{ "metadata": { "language": "Julia", "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Implementing Digital Filters in Julia" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I'm taking a short break from my [Cyclone V Tutorials](http://zhehaomao.com/project/2014/01/02/fpga-series.html) to read up a bit on digital signal processing. This will be useful background for the next project in the series, which involves real-time audio processing.\n", "\n", "Like all of the other Columbia EE and CompE majors, I took the EE department's infamous Signals and Systems course, which provided an introduction to analog signal processing. However, I never got to chance to take the introductory digital signal processing course. So other than implementing an FFT in VHDL for the final project in my embedded systems course, I don't have much experience when it comes to DSP.\n", "\n", "To make up for this, I've started reading the rather excellent [Scientist and Engineer's Guide to Digital Signal Processing](http://www.dspguide.com/) by Dr. Steven Smith. This book has very clear and understandable explanations of key DSP concepts. One thing it lacks, however, is up-to-date code examples. The few pieces of code it does have are written in either BASIC or SHARC DSP Assembly. I thought I would remedy this by writing some code examples in a modern scientific computing language. This gave me the perfect opportunity to learn more about the [Julia Programming Language](http://julialang.org/) and [IPython Notebook](http://ipython.org/notebook.html).\n", "\n", "Julia is a new programming language focused on scientific computing which is being developed at MIT. Its goals are to combine high expressiveness and high performance. Its syntax is similar to MATLAB, so if you've ever used MATLAB before, the code examples should look very familiar.\n", "\n", "The core signal processing concepts involve quite a bit of advanced mathematics. I've tried to gloss over the math as much as possible here. If you're interested in the details, I recommend reading *The Scientist and Engineer's Guide*." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "The Basics of Signal Processing\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Signal processing is the art of analyzing and manipulating signals. A signal is simply a measurable quantity that varies in time and/or space. The key insight of signal processing is that a signal in time can be represented by a linear combination of sinusoids at different frequencies. There exists an operation called the Fourier transform, which takes a function of time $x(t)$ (which is called the time-domain signal) and computes the weights of its sinusoidal components. These weights are represented as a function of frequency $X(f)$ (called the frequency-domain signal). The Fourier transform takes a continuous function and produces another continuous function. In digital signal processing, since we operate on signals in discrete time, we use the discrete Fourier transform (DFT). This takes a set of $N$ samples in time and produces weights at $N$ different frequencies. Julia's signal processing library, like most common signal processing software packages, computes DFTs using a class of algorithms known as fast Fourier transforms (FFT).\n", "\n", "To explain the use of Fourier transforms, let's look at an example. Let's examine what happens when we take the Fourier transform of several periods of a sinusoid at 440 Hz." ] }, { "cell_type": "code", "collapsed": false, "input": [ "using PyPlot\n", "\n", "freq = 440.0\n", "N = 256\n", "duration = 8 / freq\n", "t = linspace(0, duration, N)\n", "x = cos(2 * pi * freq * t)\n", "\n", "plot(t, x)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 18, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 18 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use the `rfft` function (the real FFT function), because our input signal is composed entirely of real numbers (as opposed to complex numbers). This allows us to optimize by only computing the weights for frequencies from $1$ to $N / 2 + 1$. The higher frequencies are simply a mirror image of the lower ones, and so do not contain any extra information. We need to use `abs` on the output of `rfft` because the outputs are complex numbers. Right now we only care about the magnitude, not the phase of the frequency domain signal." ] }, { "cell_type": "code", "collapsed": false, "input": [ "X = rfft(x)\n", "sampRate = N / duration\n", "f = linspace(0, sampRate / 2, int(N / 2) + 1)\n", "magX = abs(X)\n", "plot(f, magX)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 19, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 19 }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you can see, the frequency domain signal is just a single spike at 440 Hz. This is pretty much what we expected, since our time-domain signal is just a single sinusoid. Let's see what we get when we add two sinusoids together. Let's add our original sinusoid to another at twice the frequency but half the amplitude." ] }, { "cell_type": "code", "collapsed": false, "input": [ "chord = cos(2 * pi * freq * t) + 0.5 * cos(4 * pi * freq * t)\n", "\n", "plot(t, chord)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 20, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "Chord = abs(rfft(chord))\n", "plot(f, Chord)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 21, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 21 }, { "cell_type": "markdown", "metadata": {}, "source": [ "So we still see our original spike at 440 Hz, but now there's another spike at 880 Hz, which is half the height. So we see that the weights given to the sinusoids in the time domain correspond to value of the frequency domain signal at those frequencies. This is an important result, since it works the other way as well. If we can change the values at certain frequencies in the frequency domain, we can emphasize or de-emphasize certain sinusoidal components of the time-domain signal. This is the basis for all digital filters." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Basic Digital Filters" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A filter is an operation which takes some signal as input and manipulates it to produce a different signal as the output. The simplest class of filters used in DSP are convolutional or finite impulse response (FIR) filters. They are called convolutional filters because they produce the output by convolving the input with another function called the filter kernel. Convolution is an operation in which each element of the output is the linear combination of some elements of the input. The weights come from the elements of the kernel. More formally, the discrete convolution is defined as\n", "\n", "$$(f * h)[n] = \\sum\\limits_{m = -\\infty}^\\infty {f[n - m] \\cdot h[m]}$$\n", "\n", "The $ * $ is the convolution operator. The filter kernel $h$ is also known as the impulse response because it is what the output will be if the input is an impulse function (an impulse function is a spike at an origin). In the definition of convolution given above, the summation index $m$ is unbounded in either direction, but for FIR filters the kernel is a finite array (hence finite impulse response), so $m$ simply goes across the indices of the kernel.\n", "\n", "The reason convolution is used for filters is that convolution in the time domain corresponds to multiplication in the frequency domain. That is,\n", "\n", "$$f(t) * h(t) \\xrightarrow{\\mathcal{F}} F(f) \\cdot H(f)$$\n", "\n", "The $\\xrightarrow{\\mathcal{F}}$ symbol means \"Fourier transform of\". You can see how multiplying the frequency domain of the input by some known function would be useful if our goal is to emphasize or deemphasize certain sinusoids." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Moving Average Filter" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The simplest FIR filter is a moving average filter. This is exactly what it sounds like. Each element of the output is a weighted average of a certain number of elements of the input. The kernel for this filter would just be a constant function in the time domain. If $N$ is the number of elements we want to average, our kernel $h$ is defined such that\n", "\n", "$$ h[n] = \\frac{1}{N}, 0 < n \\le N $$\n", "\n", "Moving average filters are useful if you want to get clean up random noise in the input. As an example, let's take our 440 Hz sinusoid and add some small random noise to it." ] }, { "cell_type": "code", "collapsed": false, "input": [ "noise = randn(length(x)) / 20\n", "noisy_x = x + noise\n", "plot(t, noisy_x)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 22, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 22 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's apply our moving average filter and see if it cleans up the noise." ] }, { "cell_type": "code", "collapsed": false, "input": [ "mavg_n = 16\n", "mavg_h = ones(Float64, mavg_n) / mavg_n\n", "# conv is the convolution function\n", "filtered_x = conv(noisy_x, mavg_h)\n", "t = [0:length(filtered_x) - 1] / sampRate\n", "plot(t, filtered_x)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 23, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 23 }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's not too bad! It's a little bit weird on the sides because there are less points to add. This becomes less of a problem with larger inputs." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Low Pass Filter" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Moving average filters work great for removing noise, but what if we want to selectively remove parts of the signal? For instance, what if we only care about certain frequencies, but want to filter out the others. This is very common in RF communications, where each \"channel\" is a different frequency.\n", "\n", "The simplest filter of this sort is a low-pass filter. This is a filter which allows sinusoids below a critical frequency to go through unchanged, while attenuating signals above the critical frequency (hence why it is called low-pass). An ideal low-pass filter has a frequency response (the Fourier transform of the impulse response) defined as follows ...\n", "\n", "$$\n", "H(f) = \\left \\{ \\begin{array}{lr}\n", "1, & f < f_c \\\\\n", "0, & f \\ge f_c \\\\\n", "\\end{array} \\right.\n", "$$\n", "\n", "The impulse response of such a filter is the sinc function\n", "\n", "$$ h(t) = sinc(2 \\pi f_c t) = \\frac{\\sin(2 \\pi f_c t)}{2 \\pi f_c t} $$\n", "\n", "Unfortunately, the sinc function is infinite in either direction, but we can only use a finite kernel. Therefore, the filter we end up using is a portion of the sinc function centered around the origin, with the two tails on either side cut off. This is appropriately named a windowed-sinc filter." ] }, { "cell_type": "code", "collapsed": false, "input": [ "sinc_w = 75\n", "t = [-sinc_w:sinc_w] / sampRate\n", "freqCrit = 660.0\n", "sinc_h = sin(2 * pi * freqCrit * t) ./ (2 * pi * freqCrit * t)\n", "# need to fix the singularity at the origin\n", "sinc_h[sinc_w + 1] = 1\n", "# normalize so that the sum is 1.0\n", "sinc_h ./= sum(sinc_h)\n", "plot(t, sinc_h)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 24, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 24 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Of course, since this function is cut off, the corresponding frequency response isn't ideal anymore. Let's see what it looks like." ] }, { "cell_type": "code", "collapsed": false, "input": [ "sinc_H = abs(rfft(sinc_h))\n", "f = linspace(0, sampRate / 2, sinc_w + 1)\n", "plot(f, sinc_H)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 25, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 25 }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's not so great. There's a lot of ripple in the passband (the part below the critical frequency), and it goes to 0 a bit too slowly in the stopband (the part above the critical frequency). The problem here is the sharp discontinuity at the edges of the filter kernel. The DSP guide suggests that we can solve this problem by multiplying our sinc function with a Hamming window, a function which is 1.0 in the center and then rolls off at the edges." ] }, { "cell_type": "code", "collapsed": false, "input": [ "M = 2 * sinc_w\n", "i = [0:M]\n", "hamming_w = 0.54 - 0.46 * cos(2 * pi * i / M)\n", "plot(t, hamming_w)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 26, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 26 }, { "cell_type": "code", "collapsed": false, "input": [ "win_sinc_h = hamming_w .* sinc_h\n", "win_sinc_h ./= sum(win_sinc_h)\n", "plot(t, win_sinc_h)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 27, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 27 }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you can see, multiplying by the Hamming window causes our filter kernel to roll off a lot more gradually at the edges. Let's see how that affects our frequency response." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Win_Sinc_H = abs(rfft(win_sinc_h))\n", "plot(f, Win_Sinc_H)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 28, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 28 }, { "cell_type": "markdown", "metadata": {}, "source": [ "This frequency response is pretty close to ideal. The passband has very little ripple, and the stop band is fully attenuated, which is exactly what we want from a low-pass filter. The only difference between this and an ideal low-pass filter is that the slope at the critical frequency (known as the gain) is not infinite. We of course cannot expect infinite gain from a finite filter, but the gain can be adjusted by changing the size of our filter. The larger the filter, the larger the gain.\n", "\n", "Let's see what happens when we run our chord signal through the low-pass filter." ] }, { "cell_type": "code", "collapsed": false, "input": [ "filtered_x = conv(chord, win_sinc_h)\n", "t = [0:length(filtered_x)-1] / sampRate\n", "plot(t, filtered_x)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAsEAAAIUCAYAAAD7QvHoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAIABJREFUeJzsnXmUXWWZr3+n5kqNmZNKSICQIIIYEgK5DC4CDigXEG9Ag+AFdQHq7TRqM4gXo6a93dKKXNqLCkpIkE4jAYVWVESCjYphQcVWiSEkkIGkKmNVaq6kqs794/VLVSU17OEbz/k9a9UqcuqcfV722WfvZ7/f+71fJpvNZkEIIYQQQkgeUeA6AEIIIYQQQmxDCSaEEEIIIXkHJZgQQgghhOQdlGBCCCGEEJJ3UIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSd1CCCSGEEEJI3kEJJoQQQggheYdxCW5vb8eyZctw8cUXY9y4cSgoKMDKlSsjvfahhx5CQUHBkD979uwxHDkhhBBCCMlViky/wd69e7F8+XLMnDkTc+fOxfPPP49MJhNrG8uXL8cJJ5ww6LGamhqdYRJCCCGEkDzCuATX1dWhsbERkyZNwiuvvIIFCxbE3sb73/9+zJs3z0B0hBBCCCEkHzFeDlFSUoJJkyYBALLZbKJtZLNZtLa2ore3V2dohBBCCCEkTwliYtyiRYtQU1ODiooKXH755di8ebPrkAghhBBCSMAYL4dIQ0VFBa6//nosWrQI1dXVePnll3H33XfjnHPOQX19PaZPn+46REIIIYQQEiBeS/CVV16JK6+88si/L7vsMrzvfe/Du971Lnzta1/Dd77znSFf19DQgIaGBlthEkIIIYSQmEydOhVTp0519v5eS/BQnHvuuTj77LPx7LPPDvn3hoYGnHnmmdi1a5flyAghhBBCSFTq6urw8ssvOxPh4CQYAKZPn45NmzYN+beGhgbs2rULP/zhD3HKKadYjoyMxs0334x77rnHdRhkGPj5+As/G3/hZ+M3/Hz85K9//SuuueYaNDQ0UILj8MYbb2DixIkjPueUU05hWzUPqa2t5efiMfx8/IWfjb/ws/Ebfj5kOLzpDtHY2IiNGzeip6fnyGN79+495nlPP/006uvrcfHFF9sMjxBCCCGE5BBWMsHf/va30dzcfKRO96mnnsL27dsBAEuXLkV1dTVuv/12rFq1Clu3bsWMGTMAAOeccw7mzZuH+fPno6amBvX19XjwwQcxY8YM3HHHHTZCJ4QQQgghOYgVCf7mN7+Jbdu2AQAymQx+/OMf44knnkAmk8HHPvYxVFdXI5PJHLOc8kc+8hH87Gc/wzPPPIOOjg7U1dXhxhtvxLJly0YthyCEEEIIIWQ4rEjwm2++OepzVqxYgRUrVgx6bPny5Vi+fLmpsIgDlixZ4joEMgL8fPyFn42/8LPxG34+ZDgy2aRrGXtKfX095s+fj1deeYWF8IQQQgghHuKDr3kzMY4QQgghhBBbUIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSd1CCCSGEEEJI3kEJJoQQQggheQclmBBCCCGE5B2UYEIIIYQQkndQggkhhBBCSN5BCSaEEEIIIXkHJZgQQgghhOQdlGBCCCGEEJJ3UIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSd1CCCSGEEEJI3kEJJoQQQggheQclmBBCCCGE5B2UYEIIIYQQkndQggkhhBBCSN5BCSaEEEIIIXkHJZgQQgghhOQdlGBCCCGEEJJ3UIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSd1CCCSGEEEJI3kEJJoQQQggheQclmBBCCCGE5B2UYEIIIYQQkndQggkhhBBCSN5BCSaEEEIIIXkHJZgQQgghhOQdlGBCCCGEEJJ3UIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSd1CCCSGEEEJI3kEJJoQQQggheQclmBBCCCGE5B2UYEIIIYQQkndQggkhhBBCSN5BCSaEEEIIIXkHJZgQQgghhOQdlGBCCCGEEJJ3UIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSd1CCCSGEEEJI3kEJJoQQQggheQclmBBCCCGE5B2UYEIIIYQQkndQggkhhBBCSN5BCSaEEEIIIXkHJZgQQgghhOQdlGBCCCGEEJJ3UIIJIYQQQkjeQQkmhBBCCCF5ByWYEEIIIYTkHZRgQgghhBCSdxiX4Pb2dixbtgwXX3wxxo0bh4KCAqxcuTLy65ubm3HDDTdg4sSJqKysxIUXXoj169cbjJgQQgghhOQ6xiV47969WL58OV577TXMnTsXAJDJZCK9tq+vD5dccglWr16NpUuX4q677sKePXtwwQUXYPPmzSbDJoQQQgghOUyR6Teoq6tDY2MjJk2ahFdeeQULFiyI/No1a9bgxRdfxJo1a/ChD30IAHDVVVdhzpw5WLZsGR555BFTYRNCCCGEkBzGeCa4pKQEkyZNAgBks9lYr12zZg2mTJlyRIABYMKECbjqqqvw5JNP4vDhw1pjJSQJ+/YBO3e6joIQkov09QF/+pPrKAjJTbyeGLd+/XrMmzfvmMcXLFiAjo4ObNq0yUFUhAzmqquACy4AentdR0IIyTVWrADe+U7gD39wHQkhuYfXEtzQ0ICpU6ce87h6bNeuXbZDImQQL78MrF0LbN4M/PSnrqMhhOQS2Sxw993y39/4httYCMlFvJbgrq4ulJaWHvN4WVkZAKCzs9N2SIQM4pvfBE44ATj7bOBb33IdDSEkl3jmGWDDBuCjHwWeeEJutgkh+jA+MS4N5eXl6O7uPubxrq6uI38fjptvvhm1tbWDHluyZAmWLFmiN0iSt+zfDzz2mGRqpk6Vsoi//hU45RTXkUXn5z8HCgqA973PdSTx6OsTKairA845x3U08Xj9daC9HTjpJKCy0nU00enuBu6/H7jiCmD6dNfRxKOtDbjvPuCmm4DqatfRROe73wXOOAN44AHgl7+U31//uuuoCInP6tWrsXr16kGPNTc3O4qmH68leOrUqUOWPDQ0NACQzhPDcc899wxZT0yILl59VeqAL7qoXwrWrw9Hgh98EPjkJyX2bduAiJ0LndPaKjXY9fVSK/nHP7qOKDrr1wPqtHTllcCPfuQ2njj85CfA0qXALbcA3/8+cM01riOKzsMPA7fdBjz+OPCLXwBjx7qOKBr19cDVVwPl5XKzxwlyJFSGSkLW19dj/vz5jiISvC6HmDt3Lurr64/pKrFu3TpUVFRgzpw5jiIjBHjtNcminnQSUFMDTJ4sj4XAtm0iwOedB+zYEZZI/uY3Igef/jTwX/8F7N7tOqLo/PrXIjQ33gg895xktEPhV78C5swBzj0X+M53XEcTjyefBE49VbLwd9zhOppodHQA27fLPgeAk08O5/xCSCh4I8GNjY3YuHEjenp6jjy2ePFi7N69G0888cSRx/bt24fHHnsMl156KYqLi12ESggAuSAdfzygytZPPhkIpWHJunUy6ebf/x2orZUsXyisWwdMnAh86Uvy72efdRtPHF54AVi4EFi8WMppNm50HVE0slmpT/3AB4BLL5WbkFA6VB48KDccN90E/I//EU6XBVX/e/LJ/b+3bgX+Vg1ICNGAlXKIb3/722hubj5S2vDUU09h+/btAIClS5eiuroat99+O1atWoWtW7dixowZAESCFy5ciOuvvx4bNmzA+PHjcd999yGbzeIrX/mKjdAJGZbXXuu/QAHy3y+/7C6eONTXSxlEXR3w3/+7SHAoX6mXXpKJiJMnA3Pnipx99KOuoxqdvj7gd78DPvMZEeHCQpHit7/ddWSj89prMmLw3vfKqEdXF/DnP/eXdvjMz38uwn755bLPH3pI6puHmHPtFSrrO1CCs1mR49NOcxcXIbmElUzwN7/5TXzpS1/Cd7/7XWQyGfz4xz/Gl770JSxbtuxIYXQmkzlmOeWCggI8/fTT+PCHP4x7770Xt956KyZNmoTnnnsOs2fPthE6IcNytATPmSOZ4Jhrwjihvr5fYC6/XGoNt21zG1MUslmR4LPOkn+/5z0iwSHs840bJft7/vkyIW7ePJHgEHjmGaCkBHjXu2SiVlGRfA4h8B//Ifv6uOPkd08P8Je/uI5qdDZtAsaNA8aPl3+rsgiWRBCiDysS/Oabb6Kvrw99fX3o7e1Fb2/vkf9WWd8VK1YM+reitrYWDzzwAPbu3Yu2tjY899xznPBGnHPoEPDGG8dmgtvbAd/bV2ezgyV44UL5HYIYvP460NzcL8HvfjfQ2BhGGcoLL0gmUu3v888PR4Kff14mZlVUSE3z6adLWUoI/PnP/fv89NPlM6ivdxtTFI6+yZ44UUqXKMGE6MObmmBCQuKNN6QzxNESDPh/kdqxQzKSSoLr6mRoOIQepCr7uGCB/FalBCHE/vvfSxZVtUU7/3yZ+BTCktubNw8u2zjrrDAywdkssGULMGuW/Lu8XLq3hCjBmQwnxxGiG0owIQk4ul4PkEUzior8z0q+8or8Vp1pCgqAE08UWfCdl14CZs+WYWJABL6kBHjzTbdxRWHz5sHt8972Nvnt+37PZmX/nnBC/2Nnny09sVta3MUVhcZG6bKgJBiQmz/1HfCVbFbOI0c3QKIEE6IXSjAhCXjtNcnoDVzVu7hYZNL3i1R9vUwqGxj7SSf5L2OAxDhQJAsKgJkzw5DgbdskVoWq/PK9Fnv/fllsYqAEv+1t/XLsM+qYPumk/sfmzZMaeJ+7W+zdK2U/A2+ygX4JDqEGnpAQoAQTkoA33pAL69ELTMye7f/Q/Ouvi0gOjH3WLP/jBqR84KhpAzjhBPk8fObQIakVHyjBY8ZInafvEqz27UAJVp/B35r8eIuS4BNP7H/s7W+X7hBvveUmpigMJe/q383N8kMISQ8lmJAENDbKUPzR1NXJ33zmrbdkpvxAZs2SrF5vr5uYorJjx7Gxn3CC/xnJt96S7N1ACQbk375LsNq3AyV48mQp/dmxw01MUdm8Wb6T5eX9j6nVHX2W4L8tiopp0wY/rs45vp9jCAkFSjAhCWhsBKZMOfbxKVP8v0Dt2NEvAopZs2R42GcxaGmRhQ+GygS/+abfQ8Rbt8rvoSRY/c1X3nxTegMPXGq4sFCOoRAywQPrgYH+Y99ngW9slPKqo5d3Vucc388xhIQCJZiQBIwkwbt3+7scbm+vDMsfnU1Vw64+l0QoaRkqE9zSAjQ12Y8pKirbe7TAh5IJHpgFVhx3nN8iCYgEH11SUFUlUu/zDV9jo2TbC466QlOCCdELJZiQmGSzI0vw4cP+CtmePbJYwNGZ4Jkz5YLr8+Q4lXUcKhMM+F0SsW2bHBtlZYMfP/54+f/y9aYJGF6CZ8wIMxMMyPHvuwQPdX6prJRezZRgQvRACSYkJgcPysSa4SQY8PcipTJ3R0twSYlIjc8SvGOHiPrArhZAOBJ8dCkEII91d8vNia+EmglubpbOFsNJsM+xDyfBQBglV4SEAiWYkJjs3i2/h7pITZ4sv329SKns19ElBYDMoPe5y8KOHTJRqKho8OPjx0uGLFQJVn/3kd5eiW24TPDOnf5OplTHw8DOEIrjjvM7E7x7d/+55GhUyRUhJD2UYEJiogQ3VAkuLRVxPJqpU/2NG5Ch96HkPZMR0aEE62fXLinvGS4T3NPj7zGj4jp65AAItxwCYCaYEJ1QggmJyUgSXFkpP75epN56SwTg6P7GgP8Zph07jq0HVkybJsLmI729EvtQElxbC1RX+y3BwLHlM0D/Z+FrWYE6lidNOvZv06fL3w8dshtTFEaacwBQggnRCSWYkJg0NspCB5WVQ//d54vUUH12FZMn+y3Bw2WCAYnd17raxkbJpg4lwYDfHSLUPh1qaF59Fr5Ojtu9W1qMlZYe+7fjjhPZ9PHGqblZ5JwSTIh5KMGExES1Lxoqmwr4fZFSmeChmDxZWo11ddmNKQp9fUMv8qGYNMlfCVY3FkMNy6vHfb35UPt0woRj/1ZbK50KfM4ED1dX6/OCGSONNAHy/7R3r7+12ISEBCWYkJiMNFQJhC3BgJ9Ctm+fdFEYSYJ9jBvoF8mJE4f++8SJfgv8+PHHTkYE5CbQ5w4R6mZ1KEKW4ClT5KZw7157MRGSq1CCCYlJqBLc1yez+YcTSZ/bu400LK8eb2sDOjrsxRQVJSvDSfCkSf4KzZ49w+9zwO8ylJEywdXV8uOjwEeR4IHPI4QkhxJMSExCleB9+6Q2ta5u6L/7nAmOIpIDn+cTe/ZI/Xh5+dB/9zkTvGfP0BPLFBMnynHlIyNJMCDfAx9rghsbpcxkpDkH6nmEkHRQggmJSRQJVsLpE0pWhhPJCRNkiNtHCR4tdiVqPsa+d+/oInnggLQb843du0eP3ccbD0BiH+l76qvAj3Z+UZ8HJZiQ9FCCCYlBb69kx0aTYMA/OVAX/KEmOQFS9zlhgr8iWVwsQ9hDoTJ+PmZU9+wZXt4BkZpsVlY3843RyiEmTPDvOAfkBnTfvtFjD1GCS0uBceOAhgZ7MRGSq1CCCYlBc7PU1g4nkoC/WcnRSgoAf3sF793bn6keCvV5+CjBUTLB6nm+EaUcYu9ekXifUPtyJAn2NYu9d+/I31FA/u7jTRMhoUEJJiQGBw7I76FWXFOMGye/m5rMxxOHffuAggJpbTUcvvYKHk0Miotlv/sqwaNlggH/Yu/tlWNmNAk+dEgmJfqEOoZDzAQfODDy+QWQY12diwghyaEEExIDdeFRojsU6m++XaT27ZOLa8EI3/rJk/2sNdy3b+TsO+CvwEfJpgL+ZSX375dRj9FEEvAv9tAleKTzC0AJJkQXlGBCYhBFgmtqZNjet4tUyCIZZYjY1wUzRou9qkrqPH2LXcUTosCrG7mRYp8wAWhvBzo77cQUlQMHZKW7kaAEE6IHSjAhMYgiwarkwMdyiNFE0uea4BAluLNTSgVGkrFMxs/61DgS7FtGdfdu+Q6WlQ3/HBW7T7W1fX1y3mAmmBA7UIIJicGBA5K1G67nq8LHi5SaXDYSkycDBw/6t3Ry1Nh9E/gokxEBPwU+SkmBql31TeBH6xEM+FnK0doqIkwJJsQOlGBCYhClXg/w8yIVtRwC8EvIstloWWwfRTJKNhXwNxNcXi4LNwxHaam0rfMt9jgS7FMWO8pIk/r7gQP+deUgJDQowYTEINclWGX2fIr94EFZSCKKBO/dK5k0Xwg5E6wm9A3Xlk7h46ITUToshC7B3d3+1TMTEhqUYEJiEKVeDwhXgn3sbKFEMkoWu6/PrxpPJbZR+r76KsGj4eOCGVFuVisqJJMdogSriXO+zTsgJDQowYTEINRMcGenzIQfTcZ8luBQY6+uFtkaCR/LIfbvHz2bCvgZe5TvqY8TEuNkggc+nxCSDEowITGII8E+ZWlGWzJZUV0t3S18uriq2EeTYB+zY1GzqZMmSdyHD5uPKSpNTaO36gL8E0kg+vfUt17BTU2yfHll5cjPowQTogdKMCExiHpxHTvWrwtUVAlW7d18il0JVpRVtAC/JDhKCQrQ/xyfSjmilv74VhMctc0Y4J8Eqx7Bo9VhU4IJ0QMlmJAYRGlkD8hFqr1dJq/4QFQJBvzLYu/dK/u8qGjk56nPxScxiJpNVc9pbjYbTxyiHuu+1QS3tEjXhKix+ybBUeRdLX3u07FOSIhQggmJSDYbrxwC8Ecmo04uA/yrZ46aTS0vB0pK/NnngEhtHAn2KfY45RAtLcChQ+ZjikLUulrAP4GPen4pLPRvxIaQEKEEExKR1lagtzeeBPtykdq3T1bPGqnnq8I3CY7S7gqQIWTfsthxM8G+xH74sKx0F+INXxwJ9q2UI6oEA/59TwkJEUowIRGJc3H1UYLHjx+91hDwr565ubl/+Hc0fIu9qSla7L5JsIojisCr/z9fSjniZoL37fNn0QlKMCF2oQQTEhElBiFKcNRsKuDfxTVqNhWQ5/kikkD02H0r5Ygjwb4JfNyb1Z4eyXr7QFwJ9mWfExIqlGBCIhLn4uqbGMTJpvp2cY2bCfYl9p4eKaGJIpKZjPw/+hJ7yJngpiapmR2tzRjgZ+xRJdi3UQ9CQoQSTEhE1AUnihiUlEj9rS8XqbgS7EvcQLxMsE+xK7GKk8X2RcZCvuFT2dQopT++SXDUjhyAX8c6IaFCCSYkIgcOSB/d6upoz/fpIhW1SwEgz/OpvVuomeA42VT1vBBjr6iQzKtPIhknmwr4EXtnJ9DVxZpgQmxCCSYkIipLUxDxW+PTRSrqBC3Ar9n+fX3SfivXRVI9z6fYS0qkVnk0Mhm/Yo8jweo74UPscbLv6nk+La5CSIhQggmJSJyMJOCXGMQthwD8iP3gQZm5H2I9c5JyCF9iV7WpUUoKAPl8fMimAvHqamtq5LcPsce9aaqtlQl9vb3mYiIk16EEExKRgwf7L5pRqKmR1/hAEgn2IYudRCTVsLJrlNSEWMoRpzYVCDf2sjL58UGC1bki6jlGPa+lxUw8hOQDlGBCIhJXgqur/bhAHToEdHTEE0nADwlOIpIDX+cS1aWgqira830SyTiTEQG/MsFxyiEAfyYkqnNF1DkH6lzky402ISFCCSYkIi0t0S9QgD+ZYBVDXJH0QYKTZIIBP2RS1WFHLSnwRcaA+BLsk8DHlWBfBD5uJlidi3y40SYkVCjBhEQk1HKIuNnU0lJ/2rvFjd2nUo4k2dTWVukv7JpQRRJIFrsPAn/woEy6jbK0OcBMMCE6oAQTEpFQJVjJSZxJfb5MMFOxR93vvmWC42ZTAT9kMtRMcGentPYLUeAPHpTsbtSRA0owIemhBBMSkaQ1wdmsuZiiELekQD3Xh/ZLTU2yHwsLoz0/FyQ4xNh9Eck4C9oofClDaWmJf34BKMGEpIESTEhEktQEZ7PSxsglSTLBtbV+XFzjLPIBSClHebk/5RBxW+qp17kmSXeI5mbp6+ySpMe6DxIc9ya7vBwoKmJNMCFpoAQTEgG1aEPccgjAvUw2NUmtYWVl9Nf4VMoRR2gAv0o5QswEd3XFW7kMkM+or8/9DV/cyWWAXzXBceLOZPz5nhISKpRgQiLQ1iZZ3RAluLlZYom60h3gz8U17rA84E99aqg1wXEnIwL+CHxSCXa9z4H+muA4+PI9JSRUKMGERCDJxdWXFkZJsqm+XFxDjj2uBFdWSu2zLyIZt6QAcC+TSSW4pcV9KUfckSZAzjE+HOuEhAolmJAIxG1kD/iVCY6bTQ1VJAE/Finp65P9Fyf2TMaPLHaSY92nTHAmE6/0Z+xYGeVxfczELYcA5Pmu4yYkZCjBhEQgSYbJFwmOO0EL8CfDFGomWHUFiRu7DxKcNJsK+JEJjtNmDOiP3Yf9znIIQuxCCSYkAknEoLJSLsauMzVJRdKH9m5JMsE+ZMeSHC+AH1ls9f6hSnDcfe5L7CyHIMQ+lGBCIpBEagoKgKoq9xeppBLc1we0t5uJKSpJYvdBDJKIpHq+awlW+66qKvpriotlpTPX2dQkIumDBGezycshXB/rhIQMJZiQCLS0SFY36pKmCh8uUklrggG3sXd3S6uuEMsh1PvHHd72QeAPHpTjvKgo3ut8aDWWRCR96MrR1QUcPpysHML1TRMhIUMJJiQCql4vTpsxwA8hS1IT7IMEJ82m+lRSkESCfYg9btyAfE6trfrjiUPSbCrgVuDTlM+4Pr8QEjKUYEIikOTiCriXmmw2eTkE4PYCmzSbWlMjWeTubv0xRSX0coikx7prIUsSe1GR1O+7lOC0x4vr2n1CQoUSTEgEktQaAu4zwd3dwKFDybNjPmSCk0jwwNe7QLXqils+44NIJj3WXd/wAckFXvUKdkWaG77eXqCjQ39MhOQDlGDiDS0twGc/C2zZ4jqSY0nSvghwL8FpMkyAH7EnKSkA3Mcet1UX4I9IJjnWfYk9RIFPWg7hw/d0KLJZ4O67gaeech0JISNDCSbecOedwD33ABddBGzf7jqawSS9uLoe3k4qkqq9m2uRBJJngl3HnuZ4cTm8HeqxDoQrwWnq3wH/JPjOO4HPfx649lpg1y7X0RAyPJRg4gUvvwz8678C//AP8u8bb3Qbz9GEWieZVCQLCvyJPakYuM7sJc2muh7eTjoxzrVIJm0zBriPPU05xMDX+8ALLwBf+5qIcFkZ8Pd/7zoiQoYnZhMcQszwjW8Ab3sb8E//BEydCnzxi1LPWlrqOjKhpUXii4sv5RBxer4qfJDgkpL4x4APYpCmrla9Pm49sS5CFcmODrmBCFHgDx4ExoyJ35bOh/r3o/nlL4GJE4Evfxk48UTg+uulxG3WLNeREXIszAQT52SzwHPPAR/8oFwELrxQ+mb+4Q+uI+sn9JrgpLG7HiJOKjTq9a5I02ZMvd4VoU6MSzpyALiPPc2Nh3q9L6xdCyxaJKNJV1whv9eudR0VIUNDCSbOefVVYO9ekV8AOP10YNw4EWNfSFMneeiQu3ZdaSXYtcAnibu0VH5ct3dLI/Chxt7aKisNuiDp5DLAvQQnvfFQIzy+SHBrK/DSS/3n8poaYN48SjDxF0owcc7atbLs6jnnyL8LCoALLvBLgtNmJV1dpFpaJLteVhb/ta4lOKmMAX5ksdOWQ7igp0eWyk4Tu6sFM0KW4KTHemGhH0uzK377WzmGFi3qf2zRIjnHs5cx8RErEtzd3Y3bbrsNdXV1GDNmDBYuXIhnn3121Nc99NBDKCgoGPJnz549FiInNli7Fli4UGriFBdeCKxbJxdk16heu2kk2JUYJG3VBbiX4KQ3HoD7euY05TPq9S5Qx2mIZSghS3CaY72qyv1KfYrnngOmTQNmz+5/bNEioKEB2LTJXVyEDIeViXHXXXcdHn/8cXz2s5/F7NmzsWLFCnzgAx/A2rVrce655476+uXLl+OEE04Y9FhNkjMd8Y6+PuA3vwH+1/8a/Pj55wOHDwPr1wPnnecmNoW6wCSZXKZe41qCk1BTA2zcqDeeOKSNPUSBV8dLiCLpup45rQSrUo64S6ProLW3bGV1AAAgAElEQVQ12fkF8EuC162T8/XAm+7zzpOM9dq1wMknu4uNkKEwLsEvvfQSHn30UXzjG9/A5z73OQDAtddei9NOOw233norfve73426jfe///2YN2+e6VCJA7ZsAQ4cOFZ0Z8+WE+nrr4ctwZWVg7dhm9BFsq4u2WtDLYcoKpIREVexp51cNnAbtlHHatJOKNmsjDwlldE0tLUBkyYle61PErxpU389sKKqCpg7V2qFb7rJTVyEDIfxe941a9agqKgIN9xww5HHSktL8YlPfAIvvvgidu7cOeo2stksWltb0dvbazJU4oC//EV+v+Mdgx8vLweOO86PIbR8zgS7luAQyyEOHwY6O8OMPWm/2oGvcSnBVVWSdYyL69hzIRPc0gLs3g3MmXPs397xjv5zPSE+YVyC169fjzlz5qBSpcT+xoIFCwAAf/zjH0fdxqJFi1BTU4OKigpcfvnl2Lx5s5FYiX1efRUYPx6YPPnYv82ZI5lg1+S7BLua0JI2dtfZ1BBjT1tSALiNPWmVnOvYc0GC1bl6YD2w4rTTgA0b3HUOIWQ4jJdDNDQ0YOrUqcc8rh7bNcKaihUVFbj++uuxaNEiVFdX4+WXX8bdd9+Nc845B/X19Zg+fbqxuIkd/vIX4NRTh564NXu2zDZ2TejlEEPdYEShulpmend2Dp60aIukJQWA22xqmpICwO0krTQCr451lxKcJvsOuJXgo/JEkamqAnbs0BtPEtSo3VASfOqpUmqybRtw1PQeQpxiPBPc2dmJ0iGWfCr7W8+mzs7OYV975ZVX4gc/+AGuueYaXHbZZfjqV7+KX/7yl9i/fz++9rWvGYuZ2OMvf5EswVCoTLDr7EEaCS4okJW/Qs0EA+HGHmJJgXqdy9gLC5Pd9BQWisi5FPiQJTgXMsETJwK1tcf+TZ3jWRJBfMN4Jri8vBzdQ6wU0NXVdeTvcTj33HNx9tlnj9pi7eabb0btUd/GJUuWYMmSJbHej5jj0CHgtdeAz3xm6L/PmSMrx+3cKfXBrlAXmDSZmhBFcmAWO2k2OSmHDslnH2JJQdpMsOvYa2qStdQD3Ap8a2uYEtzTI8d66BK8adPQ9cCAtE2rqREJvvRSu3ERP1i9ejVWr1496LHm5mZH0fRjXIKnTp06ZMlDQ0MDAKAuwfTv6dOnY9MoM6buuecedpTwnNdflwvAcJlgNay2aZN7CS4vl5n7SQhVgl3WM6etq1UlBS5aXumIvbFRXzxxSFNSALgV+LTZVMBN7GlGmtTrfJDg118H3v72of+Wych5/tVX7cZE/GGoJGR9fT3mz5/vKCLB+OXhjDPOwKZNm9B61Ld03bp1AIC5c+fG3uYbb7yBiRMnaomPuEMNjZ166tB/P/54EU/XHSLSXFwBSnASdIikanllm5DLIdIcL4DbeuY031OXrelyQYKz2ZEzwYCc51kOQXzDuAQvXrwYvb29uP/++4881t3djRUrVmDhwoWYNm0aAKCxsREbN25ET0/Pkeft3bv3mO09/fTTqK+vx8UXX2w6dGKYV18FpkwBxo0b+u/FxTKJwnWHiFAlOG2rLvX/3NamL6aopJVg1wJfVCSjB0kINZsKuJfgEAVehwR3dAAuO4ju3w80Nw89KU5x2mnAX//qNk5CjsZ4OcRZZ52FK6+8El/4whewZ88ezJo1CytXrsT27duxYsWKI8+7/fbbsWrVKmzduhUzZswAAJxzzjmYN28e5s+fj5qaGtTX1+PBBx/EjBkzcMcdd5gOnRjm9ddHX0HopJNkQQ2XhCrBaZbABdx2ttAlwa4EPulS1YB7kQxVgltawoxdhwQDcqy7WkhVnaNnzRr+OXPmSK3/jh0yykeID1hZNnnVqlW488478fDDD6OpqQnvfOc78dOf/hTnDVgKLJPJIHPUVeMjH/kIfvazn+GZZ55BR0cH6urqcOONN2LZsmUsh8gBtmw5dpGMo5k2DYjQStooOiT4byXwVkkrkiFLsMvY09bVuqxnbm0Fxo5N/vrqamCErpdGCVXgdUlwa6s7CVaf+UhdS5Ugb9lCCSb+YOUUW1pairvuugu7du1CZ2cn/vCHP+A973nPoOesWLECvb29R7LAALB8+XLU19ejqakJ3d3dePPNN/Htb3+bApwjbNkycuYAkGVzIywqaJRQM8FpRdJle7eQM8E6jpdsVoa4bROqSGaz4cauU4JdsXOnlK9NmDD8c2bOlDZ6rkf2CBmI5TwDIUJTE3DgwOgSPG2aLMU5oFTcOvkqwYDE7qqkoLAweV2ty0ywjuMFcLffQxTJ7m45R4QYey5I8K5dkrAYqQSouBiYMQPggq/EJyjBxAlRasgAkeC+PhFhV+SzBFdWuispSNOv1qUYpD1eQhZ4V50t0ta/q9e6kuCSEvlJgg8SvHOnnKtHY9YsZoKJX1CCiROiSrBqI+2qzhCQjFy+SrDL2NPs8zFjRKBDLYcAwoy9ulq2kc3qiykK6lgPNRMc6vGi2Lmz/1w9EpRg4huUYOKELVtkAs5ok3BUdsFlXbCOi1R7u/3ln1taRAQrKpJvw5UEp73xcFnPHGomWEddbWWlm3rmtCUFQPgS7LocIk4m2PZNEiHDQQkmTogyKQ6QiRbFxW4zwaFOdGppESlJ02HAVU1w2n0OuG1NF2Jmr7NTbtTSjhwA9mPXJcGuSjnSxF1aKn2pQymHaGsDhlgCgBAnUIKJE7ZskR7Ao1FQAEyd6i4TrCM75ipTk3bxAMBdTXBra39GNCmhCryrTLAOkQw59lCPl0zG7apxbW1ywx2lHEKd81kSQXyBEkycsHlztEwwICdXV5lglR0LUQza2vSIZIjZVMCtwOs4XkLMprrOBKedBHr4sCzoYJOQRz2A/nNzlEzwiSfKb3aIIL5ACSbW6eqSzK46IY7GtGnuMsE6xYASHJ1QxUDHyIGremadmWDbEqxqedPWvwNu9nuIx7pCnZujSHBlJTBpEvDGG2ZjIiQqlGBinbfekt8zZ0Z7vstMcMgSrOvi6mKIOO3EOEAuuLZj19GvFnCTxQ79WE9b/+4yAx+yBKtzc5RyCEDO+9u3m4uHkDhQgol11AkwqgQzE5wMHZngUEsKADdioAQqxJuPkDPBuspn1LZsEuqxrti5U3p6R83Cz5wJbNtmNiZCokIJJtZRJ8CR1pkfyLRpQHOzu2VkgfyVYHVxtd3SKNSJcTqOFyDcTLASoVBFEghT4F1LcNQsMCCrxjETTHyBEkyss307MHkyUFYW7flTp8rvhgZzMQ2HDjEYM0aGaUOV4L4+mSBok1Anxqn3C1ng09TVFhXJUtcuYtfRCQWgBMeloSGZBLNXMPEBSjCxzvbt0UshAJlIAbjpLalDgjMZd0IWYnbs8GGprQ1RDELPBKetqwXcxJ52hUHAzYiNjomUgFsJ3ru3/xwdhZkz5fu9Z4+5mAiJCiWYWGfbNskGRGXiRPntSoLTrroGuKtP1VETDNiNPd/ratXrQ8xIAuHG7iITrGsipWsJVufoKKhzP0siiA9Qgol14maCx4+X364kuKJCRDgNoUqwi+yY7myqzWHX0DPBOiQ41NhLSuyvvKbzpikUCVbnfkow8QFKMLFKNisnvziZ4OJioLbWjQTraNUF2M+OZbPhS3CI9cyh1wSHeKwDemJXK6/ZjL29XX6H2A4QkO/X/v2yvH1Uxo2TeRLsEEF8gBJMrLJnjwwBxpFgQDINriQ4rdAAsg11wbOBzmFWwO4FVmc2FbAfe3m5ZBTTEGo2FXAjZDomxgH2Y1fvlbbcqrJSFiHq6UkfUxyamoDe3niZ4EyGHSKIP1CCiVXi9ghW5IIEu7i4hpwJDnGiU8jZVB2TywA3Q/O6Yrd986Hre6peb/NGG+g/J8eRYIC9gok/UIKJVZQEh5IJbm/XI8EVFWFKsIu+rzonxgHhSjAzwdEJ9eZDtwTb3u9JJZiZYOILlGBilW3bpB5s3Lh4r3OZCU47VAmEmwkuLJTPK8RMsKtyCF0iqVrF2SLUiXE9PVL3HWLslGBC3EIJJlZRnSHidltgOUQ8dImk2obt2IuLZbZ+GkLPBANhCryrbGrIsYcswQUF8ZMaM2cC+/bZL98g5GgowcQqcXsEKyjB8dB1cQXsD83rFskQY3fRnznUTLBOCXbxPS0oAEpL023HpQSPHx9/gRV1DdixQ39MhMSBEkysErc9mmLiRKCjQ35sQgm2LzW6ZEyVsdje78wE81iPippzkLYPuUsJjlsKAXDBDOIPlGBilbgLZShcrRpHCbafCdYlkkVF0q4sRIG3nQnu7ZUbTF2x22zXpftYt/091RW32p5Nkkrw9Oki/uwQQVxDCSbWaG+XOrCkmWAgbAk+dEh+bNDaKhKYdpgVcFMTrEPGADe12CFmglVtZohCpjsTHKIEjxnTvz2bJJXg4mKgro6ZYOIeSjCxhqr/ylcJBuxNBFFxpx1mBdzUBOvY50C4sdvOBOuuqx24TdPongRqe9RDx/FSUCDlP7bb6iWVYECuA8wEE9dQgok1ki6UAbiR4L4+GSLWKTU2s2O6RDLUmmAg/El9IWZTbU9INJEJzmbTbysKur+noWSCAbkOMBNMXEMJJtbYtk0yk9OmxX9tWZmc5G1KsJqEp6tPMBCmBIcqkoBdMchm9dUzl5TIkHGoIjlwm6Zpa5PzSnl5+m1VVsrnaGsCrq4+5IB9Cc5m02eCKcHENZRgYo3t26UOrLg42esnTLArwaGLQajZ1FBj7+qSCWY6Y7edCQ5xUp8SybhtuobCRS12qJnglhZZ0GXChGSvnzFDSuR6e/XGRUgcKMHEGkk7QygmTpSJdbYIWYJ119WGOLkMsCvBOo8XINzYXZRy6BRJtU0bhFwOsX+//E4qwTNnSgeRxkZ9MRESF0owsUbShTIU48YBTU364hmNkCXYRE2wrTpJnQJvUwx0S7DN2JVshzqpT+eNBxBm7LYl+MAB+T1+fLLXq2sBJ8cRl1CCiTXSZoLHjes/8drAhATb7g6hg6oqGbLs6tKzvdEItRwiFzLBOupTy8ulNMGmwOusIQfCvVl1IcFxl0xWqGsB64KJSyjBxAq9vcBbb6XPBIcqweXlMnkn1JpgwI6Q9fSIbOuUmlAl2Hbs5eVAYWH6bWUy9jPwusshmAkenbQSXFMDVFczE0zcQgkmVmhslEkUaTPBoZZDFBRIQ/tQa4IBO7GbyKaGWg5hO3ZdcQP2s9ghHuvqfULtDtHUJAvypNn3bJNGXEMJJlZQd/tpMsFjx7rJBId4kQo1O5YLJQWhZoJ1SnCox7r6rtuIvbcX6OwMOxM8dmy6BXm4YAZxDSWYWEGd6NJmgtvbge5uPTGNRnu7LDuctKXb0YQqBjbLIUyI5OHDdparZia4n1AFvqhIykJsxK56EYcswUlLIRQzZ1KCiVsowcQK27YBtbVSA5YUdcK1VRKhc6gSsHeR0rloAxC2BNuOvahIFrrQQagiCYQv8CGW/rgoh9AlwbY6zxByNJRgYoVt29JlgYH+E66tkohQL65q0YYQ6yRDl+CqqnTDwwMJXSRtCbzO7hCAvdhNSHB7uyz3bgNdmeDWVqC5WU9MhMSFEkysoEOCx46V3zYzwSFKsO6Lq8qGhyoGA7drkpBFUufIARC2wNuK3dSxbmvJZ1UTnAa2SSOuoQQTK2zfnm5SHMBMcFR0X1xt1kmGngnWLWMdHXaWlQ1d4EP+nuqceDtwu6bRkQnmghnENZRgYpxsVm8mmBI8Muo9dGf2bErwmDF6tmezs4XOtnRA/+dnY4GVULOpqq90iO3dTN3w2ZJgHTXBU6ZIDT0lmLiCEkyM09QkJ+a0ElxaKlkTSvDI6FwCV2FziLiiQvoq68B2PbPu40Vt1zShHuvqBoGxh5kJLigAjjuOEkzcQQkmxtHRHk0xdixrgkdDd4ZJbSvUkgKAsY+GiSx2iNlUtS2bsesuh7ARe2enZODTSjDABTOIWyjBxDg6Jdjm0smU4H5sSo3OuEtKpM9ziLHbXqTExLFuuvWV2jchTupra9Pfh1xt1zTqHJx2YhzAXsHELZRgYpxt2+RkP3Fi+m3ZlOD29rAlONSaYJ37HLArNSYywaZj7+szc6z39kq20CSmMsE2S390YVOC1WicjkwwV40jLqEEE+OozhA66jxtZ4J1X6Rs9PFsbZXskq5FG4BwRRIIV+BtZYJ1r1wG2BN4jnr0Y3PJZ3UO1lUOsXu3+RsmQoaCEkyMo6MzhGLcuLBrggGppzMJRXIwodczhyiStgQ+9EywzriLioCysjAlGGBdMHEDJZgYR6cEjx0bdk2w2q5JdC98AIQrkkC4WewxY2T1uRBFMnSB7+yU9msm0V2CAtgTeJWIqK1Nvy1KMHEJJZgYR3cm2IYEHzoEHD4c5nAlM8GDCVXgMxk7UmOihtzmDR+gr680YK8/s6lj3VYmuLpass9pmT5djnXWBRMXUIKJUTo6gL17068Wp1DlEKbrak0OEZu+SOludwWEm00F7MRu4qYJsCPwJjPBNmKvrNTXVxqwK/AhS7COUghAJk1PmUIJJm6gBBOj7Nghv3WWQ2SzwMGDerY3HCFLsMlMsOmWV6FmsU0cL4AdgQ/5WDdxw2eznlnnxFvAbjmEjvZoCrZJI66gBBOj6OwRDPTXoFGCh8dUTXBPj2Q8TRJqOYRJCQ4xdpsiaWKfq22bJORMcHOznnpgBRfMIK6gBBOjbNsmQ5XTp+vZXk2N/KYED49JMQhVakLMpqrt2YpdZ1ayuFiGuUM81kMWeFsSfPBg/7lYB8wEE1dQgolRtm0D6ur0rYqksg/NzXq2NxxqUkyIE+NMDhGbjN3Eog1AuNlUwF7sOlcuU9jKwIeaCQ65O4QJCd6xQxZYIcQmlGBilG3b9E2KA+xngnVmx0pK5Cfk7JjJ2E0s2qC2F6oE24jdxE0TYC8DH+KxrrZPCRZmzJByq4YGfdskJAqUYGIUne3RgP4Tr+lMcOjD2yZqgtW2TWEym9rVZTbLFPrEOBMSHGom2GZ/5hDPL4Ccf3VnggGWRBD7UIKJUXRLcFmZDN3ayARnMkB5ud7t2pLgEGuC1bZDzOyZ6LULhCuSgB2Bb23Vv89t9GdWLfV0d4ew1crw4EH9E+MAYOtWfdskJAqUYGKM7m6p85o1S+92a2vtSHBFhd7+o4D5i2s2G+4Qscns+8Dtm6CtTY6VsjK92w09E8zYhybkkabeXrn50JkJrq4GJkwA3nhD3zYJiQIlmBhj61aRspNO0rvdmho75RAhXlw7O2WCWagiOfC9dGEr9spKySLqxFYmWHc2FbA3qc9UFttk7KYl2GQ/b7VfdEowINeJLVv0bpOQ0aAEE2Ns3iy/dWeCa2rsZIJDlGBTw/IlJbJEaqhiMHD7JjA9ucyk1IR6rAPhxm7yWO/rk5thU6hzrwkJVtcMQmxBCSbG2LxZ6nenTdO73dpaZoKHw9TFNZMxPzQfsgSbPF56e6W0yBScGHcspmM30YJx4PZMHuumJHjWLEowsQ8lmBhjyxbgxBP119WGnglWF0ATmJpcprZpQ4JNLCU7cPsmMHm8qO2bItSJcb29kvEMMfaQb/hUAsJEJnj3bjsT+whRUIKJMTZv1l8PDNjJBJtoZA+EmwlW2zQdu6lFG9T2TUEJPhbT2VRTpT8Ab/hGwmQ5BMC6YGIXSnAe89ZbwM6d5uoNt2wxI8G2MsG6L1CAbDPEmmDAjtSYkDEbK/VRgo8l1GwqEPbEuIHbN4E69+pskQb0zx0xJcGdncCGDdKajhAFJTgPWbcOOOcc4LjjgOnTgRNOAJ5/Xu979PQAb76pf1IcEH45RMhiYDp2E/JeWCj9nkMUyZAluLJSVgE0tUhJ6KMegCzMoRNbElxSor8d4IQJ0ipNd11weztw/fWyb049FZg6FfjiFynDRKAE5xkPPQS8610iqY88Ajz5pNTtXnQRsHKlvvfZsUNOMqGWQ4QqwSp7ZSKLbUMMTOxzINzYTUuNqb7SQP821XLYujEtwaYzwab6kKvtm0L3ksmKTEZ/h4iDB4GFC4HHHgPuugv41a+A666T/77oIqCpSd97kTAxLsHd3d247bbbUFdXhzFjxmDhwoV49tlnI722ubkZN9xwAyZOnIjKykpceOGFWL9+veGIc5cf/Qj4+MeBj30M+O1vgauvBi67TE4M//N/AjfdBPzpT3reSw1pmcoEd3fLUrimCFWC29okS1NSon/boYokEG7spqXGVF9pwHzsIY96mJxzAIQpwYBcL3SVQ2SzwCc/KQmZdeuAz38eePe7gW98Q0Y+N2yQ65/JdnLEf4xL8HXXXYdvfetbuPbaa3HvvfeisLAQH/jAB/C73/1uxNf19fXhkksuwerVq7F06VLcdddd2LNnDy644AJsZh+V2KxbB1x7rYjv9743WJIKC4H/9/+Ak08GPvxhWdIzLa+9JhOcdC6ZrFC1aCZLIkxKzeHDevbxUJgqKQDs1ElSggcTskiGHnuIx0tJiZx3TXeHMCXBc+YAGzfq2daKFcCaNcCDD0oZxEDOPRf42c+AV16RpJDJPtzEb4xK8EsvvYRHH30U//zP/4yvf/3r+OQnP4nnnnsOM2fOxK233jria9esWYMXX3wRK1euxJ133olPf/rTeP7551FYWIhly5aZDDvnaGoSuZ03T04IQw3BlZcDDz8s8vr976d/zw0b5ISme6Y/0H8CDlWC1fZNQJEcmlBjLy2Vm1TTImlqIuXA99CNuiEzFbvpm1UTJUuA+WPdZCb47W8Hdu1Kf25vb5e636uvBj70oaGfc/bZwA9/KKJ8zz3p3o+Ei1EJXrNmDYqKinDDDTcceay0tBSf+MQn8OKLL2Lnzp0jvnbKlCn40IAjeMKECbjqqqvw5JNP4jCr2iORzUoJREsL8O//PvIw+TveIdnir341fS/bV1899u5bF6YzwX194Q5Xmlq5DAhXJIFwY89kzMaeC5lg3ZPLAN6sjsTBg/o7Qyje/nb5vWFDuu3cey+wfz/wj/848vM+9CHgH/4BuPVWYJTBaZKjGJXg9evXY86cOag86tu+YMECAMAf//jHEV87b968Yx5fsGABOjo6sGnTJr3BWmLHDuCb3wSuuAI4/XQpQViwQGpyV6/WP9z8r/8K/OQnMjQUpTThq1+VzPF3vpPufTds6D+h6UZlIUxNjlMTeUIVA5MXV5ZDHEtPj9Snhxh76BJsYnIZEP73NNRM8Mkny+eZRoLb2mTi2403Suej0fg//0cmz111FbBnT/L3HYr164E77wTe9z7glFOAt71NJqZ/6lMyKd3kwkkkGkYluKGhAVOnTj3mcfXYrl27jLzWN3bvlprb888HZsyQYZq2Nvn3ZZdJBvbPf5ahmxkzgC9/Wc9J7OWX5S737/8euPzyaK+ZORNYskTkuacn2fvu3Ss/piXYVCbY1JKmA7dp8uJqsia4rc1c/VyoYmDyeFHbDVGC1XEYqkiq9zBBqMc6YFaCy8ulW9GrrybfxsqVcrN+yy3Rnl9cDDz6qFzvrr5aT0u/3/xGZHfePLn2l5UBF18MXHKJtCV97jnggx8Exo8HLr1UJq2bnOhNhqfI5MY7OztRWlp6zONlf2sw2DnCtMyurq7ErwVkaGP7duki0N0t2b3hfoqK5CAtLwcmTgTq6uTn+OPlJ8lM+/37gR//WEoQ1q6Vu9v3vhdYtUqEtLr62Nds3Qr83/8LfP3rUrv73e8CH/hA/PcG5ET14Q8D73yn3BXHYelSOZE89dTw9VQjoe7iTZVDqH1nKhNsajUnIPyLa1+fnKzLy/Vv32TsJmf7mxRJtd0QY1ffH1OjB6FL8OTJZrYdsgQDkjxJmgnu65NSiCuukIRSVOrq5Fr97ndLEmr58mTv39QE3HyzXOfPPFMc4JJLhp4bs2kT8B//Ie3bPvxhKTH58Idlot7ChclGOLq6pLvGpk3iEwcOSExtbbJvANnumDHyU17e/99D/Xv+fHO1675gVILLy8vR3d19zONdf7vlKR/hSprmtQCwdOnNAAYXLpWVLUFNzRJUVAz+0NUa9B0dMhyyf3//awoK5Ms0a1b/z0knye/jjpOsWHe3nOhff11aj/3610B9vbx+0SLpxnDFFXLXNxLHHw9861vA3/0d8OlPy5fnU5+Sli5x6t76+qQX4r59wDPPxJf4efOA884TIU8qwUVFZnoEAzJRqKrKXCY45CHi1lYzHTmAwbGHJsGhiiQQrsCbXqTE9E2Teg8TtLebkwvT7d1MdocARIIfeSTZa595RgTwBz+I/9pFi6SG+I47ZDGp978/3ut//3sZRW1pkfe/7rqRRXbOHGnb9vnPy4T0Vatkcvr3vifJuAsvlF7Gp58ukl5aKtfyzk6goUEmEG7dKq/dtEl+tm3rH6kbM0acY9w4+Z6oWAb6TkfH4P8+mg0bpIxDB6tXr8bq1asHPdZsuuF/BIxK8NSpU4csW2hoaAAA1NXVGXktADz99D0488x5KC2VLG9xsUwyiUJ3txxkb7whd1WbN8vvl14C/u3fRj7BTJ4sB+9NN4nETpkS7T0HcuKJwM9/LnW5n/+8ZJIfeUTkNApf+ILUG/3kJ8n79H7mM/KFfu01qdOKw6uvArNnm+lVqzC5YEbIEmwjO9baKidpnZhctAEIW4JNx15cbO67ajL21lZzpT8Dj3UTmD7W/3aZ1E5Pjwi8SQk+9VSZO9PSMvSI6Ujcf79I47nnJnvv224Tmb3mGklkRUko9PbK6O2XviQdJ/7t3+InIk4+Gfja1yQD/Z//KTL/61+LR6gM7lCUlEiyac4cqWmeM6f/Z9Kk6M4D9Cf0Bo6SH398vP+PkViyZAmWLFky6LH6+nrMnz9f35skwKgEn3HGGXj++efR2tqKqgFnq3Xr1gEA5s6dO+xr586dixdeeAHZbBaZAZ/kunXrUFFRgTlz5oz43pMnJ79Ql5b2l0JceOHgv/T/0QIAACAASURBVGWzUu+6ZQvw1luS8Swpkbv6E0+U7HCcA284MhnJBi9aBHz0ozI8sny51PgWFg79mmxWJrbddZdMvrvssuTv/8EPAmPHSlnG178e77UbNpgrhVCYXDrZpNSUl8tnG2pNsHoP3XR1mVu0AQhfgnVP2FGYlDHA/H4PuRwixAmsLS3y21R3CGBwh4iFC6O/bs8eKS+4++7k1+CCAsnIzp8PvOc9wLPPjlxWsWuXdFRau1YyyF/+sjhBUgoKgAsukB9AjpPXXwcaG/tb9pWWytLPdXXiOcP5QFwyGUkYlpVJ9jhfMDoxbvHixejt7cX9999/5LHu7m6sWLECCxcuxLRp0wAAjY2N2LhxI3oGzMRavHgxdu/ejSeeeOLIY/v27cNjjz2GSy+9FMUmGtBGIJORO6z/9t+AK6+UModLLpGDdsYMPQI8kFNOAf7wB+Czn5UM70UXybDH0Rw8KK3Qvvxl4J/+Cfjc59K9b1mZ3A2vXBlvjfW+PpkRe/rp6d5/NEKVYNXyytSs4FDFwIZItrePnFVJisleu0C4IgmEG3tZmQhJiLGb3OfqnGsyE3zKKSKScReHffhh+cyuvjrd+48dK1nYnh4pixhqgdtDh4D77pNY//pXec4//mM6AR6KykrgjDOkNOOyy4DFi2Ui3ZlnigTrEuB8xmgm+KyzzsKVV16JL3zhC9izZw9mzZqFlStXYvv27VixYsWR591+++1YtWoVtm7dihl/u+1avHgxFi5ciOuvvx4bNmzA+PHjcd999yGbzeIrX/mKybC9o6REsrEXXyyt1N72NhHvd79bLrx//rMMwXR2Siu0667T874f/7h0ifjFL+SLF4XNm6VM4eyz9cQwHDbKIUJsZm+6TzAQrgRns/Id0f25hl4OEbIEj1IVlxiT/ZlN9iEHwpfg8nJJorz0ksyJiUI2K6OWUebeROGEE2R+zzXXSEb4ve+Va6663v7oR8DOncAnPgH8y7+IOJMwMSrBALBq1SrceeedePjhh9HU1IR3vvOd+OlPf4rzzjvvyHMymcygkgcAKCgowNNPP41bbrkF9957Lzo7O3HWWWdh1apVmD17tumwvWTRIskCr1wpK93ceqvckU6dKrNKb7lFyjF0MXeu1CH/4AfRJfill+T3mWfqi2MoamrkJGSCtja58TBVJ1lREebFVWU6TQy12hBJ9T66JVjtDxOLNgDh1tUCFPih6OwUaQvxJtuGBAPAWWdJbWxUXnpJyifuvltfDHV1khH+4Q9FsD/3Oan/nTlTujZ99rP6Jo0RdxiX4NLSUtx11124a4Q+XStWrBiUGVbU1tbigQcewAMPPGAyxKAoK5Mm4DfeKMM1mYzZIZGPf1z6DDc2Rpvkt26dTIozXVNUW5uul+RIhH5xNSU16qJtInYlkjYkWHdrKpOLNgAUyeEINXZb5TPZrP7yPDX6ZkOCv/e96JPjfvADSQC9+91648hkpOb32mtlfx4+bHbCN7GP0ZpgYpaiIvM1QVdfLe/z8MPRnv/SS+ZLIQCzNcEmSwoA8xdXU7Gr7HiIsZsu5QjxeAHMx26yXVeoWWwbx3pPj4wS6sZWJvjss0U6X3559Oe2t0uP3+uvN3s9zGQowLkIJZiMyNix0iv4wQdHXymsuxv44x/lLt40tbVmJ8bx4jo0ocYeugQfOmRGamzEHmKbMcCcwId8rB88KKORQ6xjpZWTT5b9r8rrRuLxx+UY0zUXhuQXlGAyKh//OLBxI/DiiyM/77/+Sy7UNiRYZYJNLOEbamZPyYZJga+qCr8mWDc2jhfATEeRUI911fDf5GpWpgQ+5GPd9GpxisJCmVfyhz+M/twHH5RWpiecYD4ukntQgsmoXHihTAZ48MGRn/fLX4oknXGG+ZhqamQiWKhSE2KGSW3bVOyq57YJckGCQ43dRNzqhoAjNseSCxIMSNvRtWtHHgHZvBn4zW+kSwMhSaAEk1EpKJB6q0cfHfnE+tRT0sbNRt2UatZuok1aqGIQugRXVuqfyKNQGUNTmT1K8NCEPOoR6vc0VyT40ktlYtxIXSJWrJB4rrjCTkwk96AEk0hcd50so7hq1dB/37VLJjGkWaUuDupEbKIumBNuhsfkELHJuE1P6qMED42pRUpCv+FT2zeByeOludmeBM+dC0yfLqvADUVXl3SF+OhHpbcwIUmgBJNIzJwpq9V84xsy8/hofvpTyRi///124lGZYBMSHHp2LNTJQibjBsxnsU1hSmqyWTudUNQiJTqxcaybPF6Ki8Ms/bGZCc5kJBv81FNDz/1YuRLYuxe4+WY78ZDchBJMInP77cCbbwKPPXbs39asAc49V89qPVFQJ2KWQ/TT1iYzt3Uv3TmQUEUSCDd2U1LT3S0TzEyPegD6Yzfdaxfg8TIUNiUYkJHFrVuB+vrBj/f0AHfdJYmZPF07i2iCEkwic8YZUvO7bJmURihefBH41a+Am26yF4vJcggbF6mODhEQnVAkRybU2E1Jja1sKmBOgkO9WTUZd1mZjMqZkmA1CmeDiy4CZs0CvvrVwY/ffz/wxhuSmCEkDZRgEot77gF27Og/+WSzwB13AO94B/CRj9iLY8wYyXiayATbqAkGBt9I6MCWSIZYEwyEKzVjxsjQcIjZVLVtUwJv+nva3S2rhOnE9PGSyZg71m1ngouLRYCfeqq/RefrrwO33AJ86lN2OhGR3Mb4sskktzj5ZBmGWrpULhCtrcDzz8tJytSysUORyZhZNS6btZvZ03kRNy3vgNmaYN3LGR+NyVpsG1Kj++bDZiZYd+xtbbJfTE6IGijwY8fq266NGz5T31PbEgxIcuWf/1lKHz79aeD73wemTgX+5V/sxkFyE2aCSWw+8xngW9+SOuBnnwUeekgmMNimtlZ/JrizU0Q4xMUPmE0dGRNi0NsrGX3TNx8m9rututqB76WL1lZpe2fyxttkKUeI39PDh+VYty3BBQUy8frMM4H//b+B004DfvELswulkPyBmWASm4ICmZF7002SjTG9hOZwmMgE26o1HPheurB5cc1m9fb0tRX7W2/p3aa6kQlRakI/1m3ceKj30kmoZUvqXGtbggFgxgzgySfdZKJJbsNMMEmMjTXkR6K2Vr8E26g1VBmMEC+uVVUiwKHWM4eYTQXMxM5jfWRCl2DdcbuUYAUFmOiGEkyCpaZGfzlEyNkxGzXBJmMPUQxsiCQQbia4uFhulHms9xO6BNvsDkGIaSjBJFhYDjGYULNjatGGEEXSxuQytX0TsZeWiqiaxJTAh3isq+2FeLz4kAkmRDeUYBIsJibG2ZBgk0PEpieLmBADG4s2ACyHOBobMgaYE3hK8PCY2OfqXEsJJrkEJZgEi4lMsI3MXshDxGr7Oifd2M6mDrUEa1JCzwSbPl4AcwJvOnaT/ZlDvGliJpjkIpRgEiwmJsbZyASr7YcoNSayYzazqb29knnWBTPBo1NVZaZPsOnYTfRnttGHHDAnweXl5stnCLEJJZgES02NtKjSuaJTW1uYdZI2+9UCemO3ObkM0B97JiNZQ5OEetMEMPaBHDoE9PSEK8HMApNcgxJMgkWdkFta9G0z1DpJm/1qgXDLIQD9WezKSr09k4ci5EwwY+8n5JGmgwfZGYLkHpRgEixKgnWWRNiYcAPov0jZyqYWFUl/6FDLIQa+nw5CzUgC4cce4vfUpgR3d+sdJWMmmOQilGASLNXV8lunBNuYtAKYu7iGGHvo5RC2ZKyzU8pedBFqNhUI/3tqa9RD59Lszc2UYJJ7UIJJsJjIBIcqBrZEEjAXe6jlELb2OaBXakLNph46JBnOEGO3LcE6Y2cmmOQilGASLKwJ7seWSAL6Z/vbnIyo3k8XNkUSCFfgecMnUIIJ8QtKMAkWZoL7Cb0cwmY2NUSRVO8RqsCHKJLqPUKMnRJMSDQowSRYysqAkhL9E+NsCZnuoW0gXAm2ITSlpUBhYZixm+jKYTsTrGuRktBHPYBwJZjdIUiuQQkmQaN71bhQM8GtrUBBgTSzN42J7JgNGVOLH4QYu26pUX2lbYlkX59M7NNByKMebW3yPS0r07fNoTAxcsBMMMlFKMEkaEKV4IoKMxlJ0/1qAf3ZMVvZd4ClHAo1ChFi7KGXQ9jqKw3o+552dwNdXZRgkntQgknQhCrBuoeIbWUkgXDLIYBwY9ctkjZLCkzFHmom2MY+Ly8X0dYVuzrHUoJJrkEJJkGjW4JtZvZ6eqTdkw5CFsmQBd5W7GpZZt3ZVGaCR6ayUjKgPT16tmdLggsK9I42UYJJrkIJJkGjU4L7+mSYONTsmE2RDLUcoqpK3z7PZu3dfBQWiggzEyyxFxXJpFjT6O7PbEuCAb03fJRgkqtQgknQ6JTgzk4RmxDFwGY2VadIAuEKfFeX3DiFmMUOPRNcVWWn/t1E7JRgQvyBEkyCRqcE2x5mHfieabFdDtHeLgKog1DFwGY2Vb1PiLGHLpLqPXUQ6rGuzrFskUZyDUowCZrqan0SbHvCDRBuOQQgLbZ0EGp3CJvHC8BMsMJ2+Yx6Tx2EWrvf3Cy/q6v1bI8QX6AEk6CpqdG3bHLImWDbk8sAvWJAkRwd3QKfyfRPuDNJSYksiR1qNlW9pw5CzgRXVEgtNiG5BCWYBE1NjVzQe3vTbytkCXaRHdMR+6FD8hOiGIRcDmGrX61CZ29p29lUgBLMhTJIrkIJJkGjTsw6LrChS3CIYuAim6pLxkLPBNs6XgD9Am971IMSTAkmuQklmASNOjHrqAu2mdkrK5NeniFmgnWKge26Wp2dLULPBNva54CZLLYNTPRnDvF4oQSTXIUSTIJGpwTbzARnMvouUqq/cYiThWzuc/U+hw/LMrBpcRE7M8F2Y9e96ETIEszOECQXoQSToNEtwWVl9iZ/6LpIdXTY628MhJ8JHvi+aWhttX+86CzlCDkTHGLs6uYrRAlubmYmmOQmlGASNLol2HZ2TMdKVLZFsqJCflOC7cpYqJPLgHAzwYC+2NV3PcQacpZDkFyFEkyCRndNcIgXV9sTtAoLgfJyvbHb2u+6SzlsS3C+Z1MBN/s91NKfjg49nXMowSRXoQSToCkvl+FoXZlgmxdXXbWGtidoAfrEIPRMsO19rktqQr3hy2bdjNiEfMOnY1EbSjDJVSjBJGgyGX1LJ4d6cbUtkoDe2IuLgdLS9NuKgs4exy4ykup90xJqNtV2/TsQrgTrrN2nBJNchRJMgiffJdh2OQSgN3bb+xwINxOs3jctLjLBOksKQj3W1fZsoOtY7+qSBW3YHYLkIpRgEjzV1fktwS7KIXRJjYvJZep90+KirhYIM3bd5TMhfk9DzQQ3N8tvZoJJLkIJJsFTUwO0tKTfjm0h0y3BqmuDDXRN0rK9z4uKpK1ZPgu8i7padbxks+m24yoTHOrEuIHvmxSVYKAEk1yEEkyCh+UQsq0Ci9/mUMshAL1ZyRDLIbq7gZ4e+wKfzaZvCWhbJAH93SHUKnSmoQQTMjqUYBI8+S7BtjOSQNix65SaEDPBrkQSSB97yJ1Q2tpktMbWzSolmJDRoQST4KEE28+mhloTDOgt5QhZJEMW+BDrmW2fX3QtakMJJrkMJZgEjy4JdlET3NmZvu9ryCIZcjmE7UxwaanUNDMTbL/+/dAh+UmD7WNd16I26txaXZ0+JkJ8gxJMgkeHBPf1Sb2ii3ZdOuokWQ4RHR1Z7MOHpbbW5vGSyegReBeZYCVQOgReLZBjC52xuxix0dEdoqpKpJqQXIMSTIJHdYfo60u+DbWqkgsJTnuRclUOEaoE6xBJF8Py6v3yORPsauQACDN2Hd9TLpRBchlKMAmempr+tk9JcSEGOiXYhYzpWMI31HIIF9lU9X4hxq7eK20rQxc3fLpipwQT4h+UYBI86gSdpiTC1dLDQPqLlKtyCCB9KUeomWAXXQoAvZlgm3W15eXSFUFH7C6OF4CZYEJyEUowCR4dEuwyE6xDJF1cXIF0F9ieHpkYGOKkvpDLIVpbgZIS+bGFrnpmlkPEgxJMyMhQgknwqIkroUpwiOUQOpbwVfIfYjY19Eyw7eMF0LffmQmOjq6JcZRgkqtQgknwhJoJ1tXH0+UQcZrYXdXVqu4QaZbwDT0TbFvGgHAzwTpu+IBwJfjgQaC2Vk88hPgGJZgEj5LgNBNXXGT2dEhwNhtuOYTLyWU9PdLiLCnMBMcnVIEvKpKljkOU4Kqq9BP6WA5BchlKMAmeykqZdJMmE6wuFDbloKgIKCtLd3Ht7JTWcK7KIULryAHoGd5ua5PPr7RUT0xRCVUkgfAFPsTOFtXV6fc5JZjkMpRgEjyZjJzs00pwVZXItE3SioGrYXkdQ8QuM8ED3z8JqjY1k9ETU1RCF8kQs6lA+th7e6WloO39Xl2dTt6zWUowyW0owSQnSLtqXEuLm2VB02ZqXImkKuUIMXZdEhyijAGMPQm6blZtn2PSSnBnp5QOUYJJrkIJJjlByBIcWi0zIBnztJNuXJdDpI3dVTb10CH5SUrImeDWVjff07Sxq++4Cwk+dCh5/Xtzs/ymBJNchRJMcoJQJTjtxdVVNhXQI/AFBbKQgk10lXK4ykiq909KqNnUQ4eAri5+T+Og9lXS76k6p7I7BMlVKMEkJwhVgtOKpKuaYECPBLuqq1XvnxSX2VQgzNh1lf6EWLbkMhM88P3jos6pzASTXMW4BDc3N+OGG27AxIkTUVlZiQsvvBDr16+P9Novf/nLKCgoOOan3HbqiHhPqBKcdta5q3IIQI/AuxTJtPudmeB4pD3WXYkkoC/2UDPBlGCSqxSZ3HhfXx8uueQS/OlPf8Ktt96K8ePH47777sMFF1yAV155BSeddFKk7Xz3u99F5YCzdmFhoamQSaDU1AB/+Uvy17e0AHV1+uKJSnU1sGlT8teHLMGuZKywUCb2pRXJmTP1xRQVHRLc0uJGaqqqpDb18GGguDj+611LcIhZbEowISNjVILXrFmDF198EWvWrMGHPvQhAMBVV12FOXPmYNmyZXjkkUcibWfx4sUYN26cyVBJ4ORrJritTRr5u7gv1FUO4YLQs9hJhcx1XS0gsSc5nYcswSFngjMZd99TQkxjtBxizZo1mDJlyhEBBoAJEybgqquuwpNPPonDhw9H2k5fXx9aWlqQTbPOKclpQpVgHXWSLrKpQLgiCYSbxU4rwS7ratPGHrIEt7bKBNAio2mnY0krwc3NbvqnE2ILo4f2+vXrMW/evGMeX7BgATo6OrAp4jjwiSeeiNraWlRXV+Paa6/Fnj17dIdKAqe2ViQ46X1SqJngkLOprgU+zU2Ty1Zd6v2ToP6fQ4zdtQS3tcnqjElQi/HYpqxMxDtNJnjsWL0xEeITRiW4oaEBU6dOPeZx9diuXbtGfP24cePwd3/3d7j//vvx+OOP45Of/CQeffRRnH/++WhN23CS5BS1tXKBSnJYZLNuM8EdHbKiVBJCz6a6ir2mJl3sBw+6OV6KiqT8JanAuxZJIJ0EFxTI/79t1P5qb0/2elc3TWo1zaTHelMT26OR3Cby4Ew2m0V3xI7bZWVlAICuri6UlpYO+/fOzs4Rt7N06dJB/77iiitw1lln4aMf/Sjuu+8+3HbbbZHiIbmPylY0N8e/2LS3iwi7kmBALpJJLjaus6n5WA6h6mpdTRZKI/Dqda4mxgHpJLi62n5LPWBwR5Ekx6yrm2wg3bHe3EwJJrlNZAn+zW9+gwsvvDDSczdu3Ig5c+agvLx8SHHu6uoCgEStzpYsWYLPf/7z+PWvfz2iBN98882oPerbu2TJEixZsiT2exL/UR91czMwY0a81/qQHWtpSS7BrkUym00mJq4FvrEx2WtdHi/qfUPMBKetT3UpkjoE3vX3NAnNzSyHIHpYvXo1Vq9ePeixZrUkoUMiS/App5yChx56KNJzp0yZAkDKHoYqeWhoaAAA1CXsSTV9+nQcOHBgxOfcc889Q9Yjk9xECWRTU/zX+iAGaSY6jR+vL544VFdLCUpHh7Qci8vBg+6yqTpEMuRMsOsbviSELMGuyiGA9OUQJ5+sNx6SnwyVhKyvr8f8+fMdRSREluDJkyfjYx/7WKyNz507Fy+88AKy2SwyA1JF69atQ0VFBebMmRNre4CUZWzdutX5jiN+MbAcIi4hi0FbG3D88drCicXAzF6IEpy2d2qomeDCQvtLVQNSz1xRkS72UCW4pQWYNk1fPHFgOQQhw2N0YtzixYuxe/duPPHEE0ce27dvHx577DFceumlKB7QMX379u3YuHHjoNfv3bv3mG1+5zvfwb59+3DxxRebC5wEh5Kp0CQ4bSbY5TBrGoHv7pafkLOpIcauJvS5qKsF0u93lzceKoYkhJoJZjkEyXWMdi1cvHgxFi5ciOuvvx4bNmw4smJcNpvFV77ylUHP/djHPob//M//RN+AHjQzZ87ERz7yEZx22mkoKyvDb3/7Wzz66KM444wzcOONN5oMnQRGSYnMGg+tHCJtJth1NhVIFrsPdbVJ65l9yATv3JnstS5FEkifxXa1ZpLaZ2lid1kTvHlzsteyOwTJdYxKcEFBAZ5++mnccsstuPfee9HZ2YmzzjoLq1atwuzZswc9N5PJDCqZAIBrrrkGv//97/H444+jq6sLxx9/PG677TZ88YtfPNJhghDF2LHpMsEhrgDmaglcIJ0Eu16OtbpaBLi9Pf7kvJAzwS6PFyDdojYtLe5Kf0pL5SefMsFdXfLDTDDJZYyvX1NbW4sHHngADzzwwIjPW7t27TGP3X///abCIjlIbW1yCS4vBwZU51ijqEjeO8lFqrdXaoJdDxEnEXgfJFjFkUSCi4tFilyQNpvqMhOcVoJDjj207hDq/5WZYJLLcDFEkjPU1iYvh3A9RJxEJF1nJNOUcvhQDjEwjji4rqtNU+Ppw7EeauxJJbinB+jsDC8TrM6llGCSy1CCSc6QphwiRDFwnU1NM0TsOnb1vkkF3nVJQWtrsiV8XR/r+ZgJVje4LiW4o0NkPA7qXMpyCJLLUIJJzpCmHMLlxbWqKkyRBNILfMiZYFekLUMJUSRdl/4AyY91l3MOgOTHizqXMhNMchlKMMkZQpXgtOUQrmNPKgYqk+yCtJ0tXGeCVRxxcR170uOlra3/9a4IORMMxN/vlGCSD1CCSc4wdmyYNcH5mgl2GbfKyiWRGtfZ1DTtulwf60lF0ocbvrSxu84Ex/2eNjX1L3BCSK5CCSY5Q5pMsKsLFJA8E0wJTo66uIeYTU2bCXYtkh0dwOHD8V4XsgT7kgmOG7taLc7VBFBCbEAJJjlDba1ccJJMAHE55JcmE6xarLkiTTmES5EE0gl8iJngw4fddikA+j/zuDd9PkhwqDXBap8nlWBCchlKMMkZ1Czm0E72aTLBNTVuMzWhiiSQTmpcy5iKIw6+iCQQ/zvqQ+xpM8GuJFid2+KOkjU1sTMEyX0owSRnCPVkn3TxA9cyBoRbDgEk3++uY6+slBufUEUSCDf21lbpVBGHlhZZ0r2w0Exco1FeLsvKx50v4To5QIgNKMEkZ0giwT09MvPc5cleZZiy2Xivcy1jQLgiCSQT+GzW/c1HQUGyEhrXi6sMfO+kEhx3dT+dJC3lcC2TmUyy+RKu4ybEBpRgkjOobG6cjIe6GLvMBNfWAocOAV1d8V7ng0immTHvOotdUxNfJLu65MbJh/0ecjlEknZdVVXusqlAuthdy2SShYRcj5ARYgNKMMkZkmSCfVgaVL13XJn0QYLVxTXULHZcoXG9yIciSQbeBwlOM0nLtZAljf3gQfcSnGRJeR/knRDTUIJJzlBdLUN/cU72PjSEVxfXuJkaH7KptbVSI9neHu91vkhwUpF0HXuSTLD6f3XZDrCsDCguDm/yKpBO4F0fL0kywT7sc0JMQwkmOUNBgZy0DxyI/holzK7LIYD4FykfRFLFHufGo69P6ip9EPgk+xxwH3sSgW9udr/4QSaTLAPf1OReyJL2Z/ZBJuNmgvv65Dw6bpy5mAjxAUowySnGjwf274/+fB8ywbkgwXFiVxOLfIg9SfYdcB97kkywL4sfJKkj90Ekk7Z386EcIm4m+OBBEeHx483FRIgPUIJJTjF+fLxMcHNzf3bKFaHXBAPxL7CAH7G3t8dbvcyHkgIgWSbYl4lOSSXYdewVFTIxL0SBj3vDp86hlGCS61CCSU4RNxPc1CQX5QKH34TKSnn/OBcp1arLtUgmyQT7MEELSBa7DyMH6v1DrfFMUg7hQ+zqZjnEmuC45RDqHMpyCJLrUIJJTjFuXPxyCB8urjU18aSmvV2GK12LpLq4J2lL51oMkrTUa2qSLHBRkZmYojJ2bPzZ/iFngn2oCQbiC3w26085hCpxiII6hzITTHIdSjDJKZJkgn0Qg9raeGLgi0iWlclPqOUQQPyWej4cL0la0/kSe6g1wUD82NvaRDxdx15b2z96FAVKMMkXKMEkp0gyMc71BQqInwn2RSSB+JNufCopAOJngn0QybFjpTVdnNXLfDnW45ZyHDoEdHT4sd/jSrD6/3T9PY17w7d/vyy3XF5uLiZCfIASTHIKNTEuaobMF6mJKwY+SXDcesMDB4CSEmDMGHMxRSFpOYQPx0vIsY8bF2/yqjrWfRD4uBLsS+xxb/jYHo3kC5RgklOMGyez/dvaoj0/1OyYL/1qgfixKxlz3aqrslJm+4daDgGEKcFx65l9WNVRkTQT7Dr2JJlglkKQfIASTHIKdeKOWhLhkwTHubgqMfAhW5Ok/ZIPcWcy8bPYPokkED32vj4/JmgB8tl3dgJdXdGe74tIAvEF3pfY43ZCoQSTfIESTHKKuBLsi9TErQk+cECWn3W5+pcibk2wL/scCDf2uBLc0iIlQiHGrj4fH2JPWsrhumwpbheX/fv9uFElxDSUYJJTKAmOcqHKZv3KBIdYUgAky6b6coENNRMct8bTp5IC9dlHlUmfYk+SOMTMuQAAIABJREFUCS4pkQ4qLikqktZ+Uc8xBw4wE0zyA0owySnUBTZKJrizU2ae+yI1ccohfCkpAJKVQ/iwz4F4UpPN+iPBhYVSDx5iNjVJJrigQGq4XTNunHSqiFPK4cNS1UC8Y53lECRfoASTnKKyUsoEokiwL/V6gAxXxlnCN2QJ9ikTHKccor0d6OnxQySBeFKjnudD7HEzwWrFNZerOipU7FH3uw9LmyvifE8pwSRf8OC0Qog+MpnovYJ9GmZVMUTNBvuSkQQkjpaW6KtR+ZQJ/v/t3XtwFFW+B/BvTwiZkAQICUkmBCRgIShi5LWCCgavFI/9A0Vc0RLBpeS6K66UKKxQW8vKXe9FRN3d4AMuRa27i7h4a9fXumiJ4aGXV4JaQmDlHZIIMSCvPCA5949zO5PJvHogM/Pr6e+nagrS6ZmcmdPd853fnD4dyXAISUESiCwES/rAdyWVYEmvORBZ2yW85oD1bb2pSc8/LeWDKlE0MQRTwrEagiUFg0jP3pZWCTYvD2uFtABv9TW3cwiW9IHPnCM6kjHBEtoNXFkVW0rbrW4v5nNjJZicgCGYEo7VM7hra/W/2dnRbY8Vdq4ERxLgzamxpAR4uw4pACJve9eueiyxBD162LOaGmklWMq0dID14gBDMDkJQzAlHKsH+1OnvOvHmzlu0K6VYMBa26UFSXOcpJWhHNLaHulwCClhDNBtt2s1FYh8PLMEPXt6j3mhmMdOKccXomhiCKaEE0kI7tFDTx8Ub3YfDgFYa7sZHqS0PTNTB2ArVxiUNKQAiLwSLCW8A/atBKek6Lm57RjgIw3BEooDRNHGEEwJJ5IQ3LNn9NtjRSST2dfXA42NckJNJF8RS6umRjLf7unT3tlHJIg0BEsJY0BklWCJbbfj696zpz7hrbEx9HrmsVPKPkoUTQzBlHBycoCTJ8OvJykEJyXpN51IxuxJqaaa86Dase3mG73VoRySgoEZxpQKv66kGRaAyCrB0qbrsnrOQUuLXk/COQeA91gXrhp88qR+jlI+7BFFE0MwJZy8PF3xuHgx9HqSQjCg3+jNk/VCkRYkk5J0W6y0XVolONIqtpR2A7otzc3Wh3JIa7uVINncrNeTtJ9aDcE//KDbLyXAWw3BNTX6GErkBAzBlHByc/W/330Xej1pITg7O7L5jSWFmuxs6yFY2pACwFqokRgkAesBXsrX8oD1SrBZ6ZZSTQWsD4cw92Upbbcagr/7znsMJUp0DMGUcMwDeE1N6PWkhWC7VoIB6yFY0oUyAN0Wl8t6gJfWdsBaIJO2rVsdyiFpGkNTpFMwshJMJBdDMCUc8wAeqhKslLxgYLUSbL4BS6rsZWdbO/Nc0iWTAR2As7Kst92OIfjyZZlDCpqb9bClUMx+kRSCrQ7lkFYJ7tJF31gJJvJiCKaEk5Wlx6mGCsEXLuiLNkgKBlYrwadPAxkZcoYUAPp1tGMlGLA+dVRtrZyqHuANV+FedzOMSdrWrQ5DMZ+bpLZbHcohrRIMWNvWGYLJSRiCKeG4XPpgH2o4hPlGIOnNNZJKsKRqKhDZmGBpbbcagk+dkhUOunfXc1yHa7vEbd3cBsKFydpaPfOIpA9OZggOd4GV2lr9YbVz59i0y4pw23pjo35uHA5BTsEQTAkpLy90JVhiMMjO1gG3uTn0ehKrqVZD8Pff2zMENzbqs/1zcmLTJisMw9p0gBK3dXMbCPehr7ZWryvlcs+A9wIrZ8+GXu/77+UMhTCF29bNbUnShz2iaGIIpoSUm2u/EJyVpccqh5uzVmo11cpE/CdPygqSgLUQLHF7AXR77BiCzW3AStsltRuIrIotaSgEEH5bN4+ZrASTUzAEU0LKy7M2HEJSpcbqGE+plWAgdNuVkjne0EqQNH8vLcBbrQQnJ3uvSihBero+SSvcNIa1tbL2UcB6FduOlWDzmCltHyWKFoZgSkhWKsHdugEpKbFrUzhm1Sjcm+vJk/KqY1ZC8Llz+mREaUHSDAahpuuyewjOztbDJySx0naJIdhsT7hvD+xaCTYMeccXomhhCKaElJsbvhIs7UBvtRIstZoK2HO8Yc+ewKVLocd4ShxSAFgPwdLaDYT/oArIbLv5QciOVeyePfUwjkuXAv++pkYHd0kzzxBFE0MwJaS8PD0N2oULgX8v8c3VytesLS3yZikArAV4MzRIa7vVAN+1K+B2x6ZNVuXkWBvPLG1bB6yFYIlB0u3W3yKF+/Dx/fcyK8FA8P30u+84HpichSGYElK4SydLDAbmuM1QQdKcPUJakExP11NBWQnB0oYUWA3B0rYXQLfp++/1BTGCkbitA/YdDgGED/BKyR0TDAR/3SV+y0QUTQzBlJDMakawIRHHjwMFBbFrj1XhphqTWk01jPBtP3lST3UlcWYLIHwIlhbeAW+bQr3uUkNwuCDZ0ACcPy8vSALh2372rP5gIq3t5jGvsjLw73nJZHIahmBKSGZIDBaCjx0D+vSJXXusysoKPRxCaggGrJ10k5OjL2YiifmVdai2nzolOwSHqqhKD8HBTkiUeLU4U7gQLPFqcQDg8egLrBw7Fvj3NTUyjy1E0SLs7YioY2Rl6SmYjh71/93Zs3ou3muuiX27wrFrJRiw1naJQTI5WU85Z+dKcLAQ3NKiP1RJDJI5OUBTU/ATEs1tSVo1FQgfgs0PstLanpSkq8GBjostLTocSzwuEkULQzAlJMMACguBQ4f8f2dWQexaCU5N1WNwpbESgiWGd8DalbTsGIJPn9ZjyCWG4HDj9u0cgqVWggF93AtUCa6p0UNQCgtj3yaieGEIpoTVrx9w+LD/crMKIrHikZ0dfkhBbq68OV8BHchCBQOpQRIIHYKVkntiXFqa/lAULARLndoNCD/VmPmcJLY9N1cH3WCXODdfd4kh+JprAodg81jZr19s20MUTwzBlLBCVYI7dZJ5Akh+PlBVFfz3kqupvXoFP+EGkN32UCH4wgWgvl5ugA81TZrkEGxuC8EC/PHjerYUid965Obq4QPBvvmoqtIngEqbUg/QleBAwyHMY2XfvjFtDlFcMQRTwjIrwe1PvDl6FOjdW4+Pk6agQF9ZLdg4SclBsndv4IcfdPsDkdz2UBdXMYOk5BAcasorQObrnpmpP4wGqwRXVuptSqJwQzkqK2XOPgPoSnBVlf8FMw4f1s8rLS0+7SKKB4ZgSliFhXqMW/twc/SozPHAgK6mAsCJE4F/L/XkMsAbWAJVgxsadLCX2vY+fXTlMRCpl0w2hQrBx47pUJOZGds2WeFy6Qp1sCB5/Lh9Q/CJE959WZo+fXQVu/0x5tAhjgcm52EIpoRljm1rPyRC8hnQVkKwxKoeEHoOUqmXTDb16aNPSAx0hUFzeIrE4TOAblew7cWcClDiGHJAbw/BArzkaqqdQ7B57Gs/LvjQIY4HJudhCKaEZY5ta39ynORKcH6+/jdQkDRP0JIaJM03/UAVVclfywPe7SFQ248c0dPtSZylANDbeaAxnoDsbR0IPcuC5Epwly56rLIdh0OYr2n7bebwYVaCyXkYgilhpafrr4rbVoIvXdKVPamVYLdbh61Alb0zZ/S8qlKDZOfOum2BgqS5TGp1zAyKgc6aP3JEB02p1dS+ffUJWufP+/9O6kVhTAUFgbeXxkb9gU9qkASCB/hLl/Ryqdt6Wpo+xrTd1hsb9TGHlWByGoZgSmiFhb6V4MpKXVGVHAx69QocgqVXUwFdZQpUxT50SH8okThLAaBfc8MIHYKlMtsWqBoseegPoENXoBlczO1faiUYCB6Ca2r0MUZqCAb8Z4g4elS3mZVgchqGYEpo/foBBw96f96zR/87aFB82mNFQUHgIGkGA3PIhETBKnvmeEOp1dTkZP26BgqSdgnBR474Lr94UVeIJX/g69cPqKvT33K0ZW5DkivBwaYENJdJbvugQd5jIeA9RrISTE7DEEwJragIKCvTwwgAYNs2XV2SXGEKVgk+eFCfUS+5sheqEiz9DTbQRQSUkh+CPR4d4tuHYDNISg/BgP+4fTsEyXBVbMmV4FtvBcrL9QclANi+Xc8gIvm4SBQNDMGU0MaN02f879ypf962Tb8BSBYqBPfpo8feShWuEixZoMvJnjmjp3aTHIKTknTb24dgs6pthxDcPkwePw507y7zQhmm/v319mJ+wDadOKHH9kucls50663A5cvAjh36508/BYqL9YdsIifhJk8J7eab9VWnPv1UX/Vr9275IbigQI81bP/mevCgfuOVrHdvHRrbXuyjuVkHNDuGYDNYSg7BgG5f+xB87JgefiK5mpqVBXTt6h+CJV8ow9S/v55vt/0QGnNmCKlDfwDghhv0675tmy4S/O//6oIBkdMwBFNCS0oC7rhDh+CdO/WZ29JDsPk1anW173I7hOBAcwWfOKFfdzuE4OPHdbAx2T0E5+froRJSGUbgYQXHj8sO74B3X2x7zgEge45gU1ISMGoUsHWrDsKXLjEEkzMxBFPCGzcO+Pxz4O23gYwM4MYb492i0AJdMEMpe4Rg86v3tmM8zYBjhxBsTm9lkj5HsClYCJY8FMIUKAQfOSK/7QUF+gOGHUMwANx2G/DFF/q4mJcHDBwY7xYRxR5DMCW8f/s3PbSgpAS46y6gU6d4tyg088S3tm+utbXAuXP2CMHduvmfeW4Ysk/oA7yhq22YlD5HsCnQXMF2CJKA/wwuDQ3A3r3ATTfFr01WJCXp1719CD54UP62DgDjx+tjyn//tz5GSt/GiaIhqiG4pqYGCxcuRHFxMTIyMuByuVBaWhrRY5w4cQL33XcfMjMz0a1bN0yZMgWH259KTBTC9dfrisfevcD69fFuTXgZGToYfPmld5n5Ris9BBsGMGwYsGuXd9mhQ7oy5nbHr11WXHedruzt3u1ddviw/KEQgP80ac3N+uz/IUPi1SLr+vXT42ovX9Y/f/WV/v+wYfFtlxX9+/t/WD1xQs9KI93IkfqCJKWlwEsvxbs1RPER1RBcUVGBZcuWobq6GkP+/2hsRPBx8/z58yguLsaWLVuwaNEiLFmyBOXl5Rg7dizq6uqi1WxKQLfcoufGlF4FNhUV6RBjsksIBoDhw32D5MGD8odCADqkDxumh84AegjKjh3yh88A+kQnw/Ce7b93rz45cdSo+LbLin79dOg1ZxXZvVvvp3YI8O1DsPkNiB1CMKBPTBwzRv5wH6JoiWoIHj58OOrq6lBRUYF58+ZFfP+VK1fi22+/xfvvv4/58+fjySefxMaNG1FdXY0XX3wxCi0mkqGoSL+hKqV/PnhQX20tIyO+7bJi2DAdaE6e1O3ftk3P0mEHo0bpbw0AoKJCjw8uLo5vm6zIzNTbzKZN+ucvvtBf148YEd92WWEGxq1b9b+7dwODB8v/5gDQIfjQIe9+umePviyxHT6sElGUQ3B6ejq6d+9+xfffsGEDRo4ciWFtvhe77rrrcOedd+Ltt9/uiCYSiVRUpK+kZc6yYIeT4kzDh+t/d+8Gvv5aP4fJk+PbJqtGj9ZDCqqrdaDs1En+bCKm4mLdZqV0CB4yRPY8u6bcXP3B6cMP9c+7dtljKASg98n6eqCqSv+8Z49+3ZOS4tsuIrJG7IlxLS0t+OqrrzDcfEdtY8SIETh48CAuXLgQh5YRRZ9ZHTOrwZ9+ao+qHgAUFurK5O7dwAcf6MrYmDHxbpU15vCBL77QgXLkSHsESUCH4BMngG+/1UM67DAUwjR5MvDRR/rEvm++8X6Qks5sp1mB37PHPkMhiEhwCK6rq0NTUxM8Ho/f78xlVebHb6IEU1AA9Oih31TLynQ1dcqUeLfKGvPkuHffBf7nf/SMHCkp8W6VNb166Ys0/OMfwGef2WMohOn22/UVv9asAQ4csF8IPnMGWLjQPifFAXoe5pEjgb/9TVeEKyoYgonsxPJpQkopNDY2WlrX3QGDuerr6wEAKQHePc3HN9chSjSGocfRbt+up3fLzNQhxy4WLgTuvltPwTRnTrxbE5l77gFeeUX/304huFs3XZn8z//U/7dT24cP12PeS0qAqVOBoUPj3SLrpkwB/uM/dPW9udk+49+JKIIQXFpainEWLylTUVGBAQMGXHGjACA1NRUAAgbvhoYGn3UCefLJJ/3GI0+fPh3Tp0+/qnYRxcq0acC//zuwebN+o5V85a/27rxTz1Tw8ss61NjJihXArFm6qmenIAnoKvDBg3r4yVWcjhFzLhfwX/+lPzTNnWuvOWunTAGefVZ/6Lv2WnvMakEUa+vWrcO6det8lp05cyZOrfGyHIIHDRqEtWvXWlo3Ly/vStvTqkePHkhJSUF1+2vHAq3L8vPzg97/5ZdfxlA7lROI2nn0UR1oXnhBVyftZuBA4LXX4t2KyLlc+kIN0i/WEMgNN+ibHc2aFe8WXJmBA/Xt3Dng44/tM/SHKJYCFSHLysp8Jj6IB8shODc3FzNmzIhmW3y4XC7ceOON2Llzp9/vtm/fjv79+yMtLS1m7SGKNcPQ1bFp0+xzohCR0xiGPqnP7dYzXRCRfYg5Me7YsWOoqKjwWXbvvfdi586d2N1m5v39+/dj06ZNmDZtWqybSBRzhqFnhbDT18NETnPNNQzARHYU9etnLV26FADwzTffAAD++Mc/YvPmzQCAxYsXt643Y8YMbN68GS0tLa3Lfvazn2HVqlWYPHky5s+fj06dOmHFihXIy8vDU089Fe2mExEREVGCinoI/tWvfgXDMKCUgmEYWLNmDQB9+eS2IdgwDL9LKqenp+Ozzz7DvHnzsHTpUrS0tKC4uBgvvfQSsrKyot10IiIiIkpQUQ/BbSu7oWwyZxtvp1evXrw6HBERERF1KDFjgomIiIiIYoUhmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiBwnqiG4pqYGCxcuRHFxMTIyMuByuVBaWmr5/r/+9a/hcrn8bqmpqVFsNREREREluqiG4IqKCixbtgzV1dUYMmQIAMAwjIgf57XXXsOf/vSn1tvatWs7uKUUK+vWrYt3EygE9o9c7Bu52DeysX8omKiG4OHDh6Ourg4VFRWYN2/eFT/OvffeiwceeKD19pOf/KQDW0mxxIORbOwfudg3crFvZGP/UDCdovng6enpHfI4LS0tOHv2LDIyMq6okkxERERE1JYtTozr168funfvjq5du+Khhx7CyZMn490kIiIiIrKxqFaCr1aPHj0wd+5cjBo1CikpKdi8eTNKSkqwY8cO7Nq1CxkZGfFuIhERERHZkOUQrJRCY2OjpXXdbvcVN6itJ554wufnu+++GyNHjsSDDz6IlStXYsGCBUHvu2/fvg5pA3WsM2fOoKysLN7NoCDYP3Kxb+Ri38jG/pFJRE5TFm3atEkZhmHptn//fr/7//Wvf1WGYajS0lKrfzIoj8ej7rrrroC/q6qqUvn5+QoAb7zxxhtvvPHGG29Cb/n5+aqqquqqc+GVslwJHjRokOWpyfLy8qw+7BUpKChAXV1dwN95PB7s2rUL1dXVUW0DEREREV05j8cDj8cTt79vOQTn5uZixowZ0WyLJUopHDlyBMOGDQu6TrxfVCIiIiKSTczsEMeOHUNFRYXPslOnTvmt9+qrr6K2thYTJkyIVdOIiIiIKMEYSikVzT+wdOlSAMA333yD9evX45FHHkHfvn0BAIsXL25d74477sDmzZvR0tLSuqxLly64//77MXjwYLjdbmzduhXr169HUVERtm3b1mEn4BERERGRs0Q9BLtcLhiGAaVU67+Avnxyc3Nz63rFxcXYvHmzz7JHH30Un3/+OY4fP46Ghgb07dsXU6dOxaJFi5CWlhbNZhMRERFRAot6CCYiIiIikkbMmGAiIiIioliJawhubGzEggULkJ+fjy5duuCWW27BJ598Yum+Z86cwaOPPoqePXsiPT0d48aNQ3l5ecB1P//8c9x2221IS0uDx+PBL37xC1y4cMFvPaUUli1bhsLCQqSmpuKmm27CW2+9dVXP0c4k9c+RI0fgcrkC3t5+++2rfq52E4u+2bhxI376059i8ODBSEpKQmFhYdDH5L7jJalvuN/4i3b/1NfXo6SkBOPHj0d+fj66du2KoUOH4rXXXvM558XEfcdLUt9w3/EVi+Pab3/7W9xyyy3IyclBamoq+vfvjzlz5uDYsWN+63bYfhOX2Yn/3/3336+Sk5PVM888o1atWqVGjx6tkpOT1datW0Per7m5WY0ePVqlp6er3/zmN6qkpETdcMMNqmvXrupf//qXz7rl5eXK7XarYcOGqddff10tXrxYud1uNXHiRL/HXbhwoTIMQ82ZM0etXr1a/fjHP1aGYai33nqrQ5+3XUjqn8OHDyvDMNSDDz6o/vznP/vcjh492uHPXbpY9M3MmTNVamqquu2221Tv3r1VYWFh0MflvuMlqW+43/iLdv98/fXXyuVyqfHjx6vly5erN954Q91zzz3KMAz18MMP+z0u9x0vSX3DfcdXLI5rU6dOVY899ph65ZVX1Jo1a9T8+fNVt27dVF5enqqtrfVZt6P2m7iF4O3btyvDMNSLL77YuqyhoUFde+21avTo0SHvu379emUYhnrnnXdal506dUplZmaqBx54wGfdiRMnql69eqlz5861Llu9erUyDENt3LixdVllZaVKTk5Wc+fO9bn/mDFjVO/evVVzc/MVPU+7ktY/5gGpbXucKlZ9U1VVpS5fvqyUUmry5MlBgxb3HS9pfcP9xlcs+qe2tlbt3bvX7/6PPPKIMgxDffvtt63LuO94Sesb7jtesTquBfLOO+8owzDUmjVrWpd15H4TtxD89NNPq+TkZJ/wo5RSzz//vDIMQ1VWVga977Rp05TH4/FbPmfOHJWWlqaampqUUkr98MMPKjk5WS1YsMBnvaamJpWRkaFmz57duqykpEQZhqH27dvns+66deuUYRhhP+0kGmn9Yx6Qli9frs6fP68aGxuv5unZWiz6pr1QQYv7jpe0vuF+4yse/WN69913lWEY6v33329dxn3HS1rfcN/ximff7Nq1SxmGod58883WZR2538RtTHB5eTkGDBiA9PR0n+UjRowAAOzZsyfkfYcOHeq3fMSIEbh48SIOHDgAAPj6669x+fJlDB8+3Ge95ORkFBUV+YxJKS8vR3p6OgYOHBhxexKRtP4xLVmyBBkZGUhNTcXIkSPx8ccfR/zc7C4WfRNpe7jvaNL6xsT9Rotn/9TU1AAAsrOzfR6T+44mrW9M3Hdi3ze1tbWoqanBli1b8MQTT2DAgAG45557fB6zo/abuIXg6urqgJc2NpdVVVVd9X2rq6t9lreVl5fn8zeqq6uRm5t7Re1JRNL6JykpCePHj8fy5cvx3nvv4aWXXsLJkycxceJEfPjhhxE8M/uLRd9E2h7uO5q0vuF+4yte/dPU1ISXX34Z/fr1a32jNh+T+44mrW+473jFsm9qamqQk5OD/Px8jB07Fo2Njfjss8/QpUsXn8fsqP2mk+U1O1h9fT1SUlL8lptXgauvrw9634aGBkv3Nf8Ntm7bv3E17UlE0vqnd+/e+Oijj3zWeeihh3D99dfjqaeewqRJk8I9pYQRi76JVXsSjbS+4X7jK1798/jjj2Pfvn348MMP4XJ5a0/cd7yk9Q33Ha9Y9k1WVhY++eQTNDQ0oKysDCtWrMCkSZNQWlqKjIyMq25Pe3GrBKempqKxsdFveUNDQ+vvr/a+5r/B1m37ySI1NbX1/pG2JxFJ659AMjMzMWvWLOzfv99RFZNY9E2k7eG+o0nrm0Ccut8A8emfF154AatXr8bSpUsxYcIEv8fkvqNJ65tAnLrvxLJvkpOTMW7cOEyaNAmLFy/GBx98gD179uD3v/+9z2N21H4TtxDs8XgCbkTmV+T5+flXfV+zNG4ub79u27/h8XhaxwVF2p5EJK1/gikoKAAA1NXVhV03UcSibyJtD/cdTVrfBOPE/QaIff+sXbsWCxcuxGOPPYZnn3024GNy39Gk9U0wTtx34nlcGzVqFDweD3bs2OHzmB2138QtBN988804cOAAzp0757N8+/btAICioqKg9y0qKkJZWRlUuys+b9++HWlpaRgwYAAAYPDgwejUqRN27tzps15TUxP27Nnj8zduvvlmXLx4Efv27Yu4PYlIWv8Ec+jQIQBAz549wz+pBBGLvom0Pdx3NGl9E4wT9xsgtv3z97//HbNnz8bUqVNRUlIStD3cdzRpfROME/edeB/X6uvrfYaqdOh+Y3keiQ5mzju3fPny1mXmvHOjRo1qXVZdXa327dunLl261LrMnHduw4Z0fXGDAAADJUlEQVQNrctOnTqlunfvrqZPn+7zdyZOnKjy8/MDzkP7z3/+s3VZZWWl6ty5s3r88cdbl7W0tKjbb79d9e7dW7W0tHTME7cJaf1z6tQpvzZWVlaqzMxMVVRUdHVP1mZi1TdthZsnmPuOJq1vuN/4ilX/lJaWKrfbre68886QU0Bx3/GS1jfcd7xi0TcXLlxQFy5c8PvbGzZsUIZhqBUrVrQu68j9Jq5XjLvvvvtar0Dy+uuvq9GjR6vOnTurLVu2tK7z8MMPK8MwfK7Q0tzcrEaNGqUyMjJ8rkDSrVs3deDAAZ+/UVZWptxutxo6dKh69dVX1aJFi1RqaqqaMGGCX3ueeeaZ1iuQrFq1Sk2ePFkZhqHWrVsXvRdBMEn9M3PmTDVmzBi1ZMkS9cYbb6hnn31WZWVlKbfbrUpLS6P7QggUi7758ssv1XPPPaeee+45dd1116nMzMzWn9977z2fdbnveEnqG+43/qLdP0eOHFHdunVTXbp0UStXrlRvvvmmz+2rr77yaQ/3HS9JfcN9x1e0+6a8vFxlZWWpn//85+p3v/ud+sMf/qBmzpypkpOT1ZAhQ9TFixd92tNR+01cQ3BDQ4N6+umnlcfjUW63W/3oRz/yuUqYUnpDdLlcfpcpPH36tJo9e7bKzs5WaWlpqri4WO3evTvg39m6dau69dZbVWpqqsrNzVVz585V58+f91uvpaVFPf/886pv374qJSVF3Xjjjeovf/lLxz1hm5HUP+vWrVNjx45VOTk5Kjk5WeXk5KipU6eq8vLyjn3SNhGLvlm7dq0yDEMZhqFcLpdyuVyt/581a5bPutx3vCT1Dfcbf9Hun02bNrX2hdlHbftqyZIlPutz3/GS1Dfcd3xFu29qa2vVnDlz1KBBg1R6erpyu91q0KBB6pe//KXfRTqU6rj9xlCq3UANIiIiIqIEF7cT44iIiIiI4oUhmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiByHIZiIiIiIHIchmIiIiIgchyGYiIiIiBzn/wD+PIAAVnly8gAAAABJRU5ErkJggg==", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 29, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 29 }, { "cell_type": "markdown", "metadata": {}, "source": [ "This looks pretty close to the original single sinusoid signal. But again, the edges are weird. Let's see what it looks like in the frequency domain." ] }, { "cell_type": "code", "collapsed": false, "input": [ "filtered_X = abs(rfft(filtered_x))\n", "f = linspace(0, sampRate / 2, length(filtered_X))\n", "plot(f, filtered_X)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 30, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 30 }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's pretty good. It's a bit messier than the original, but there is clearly only one major spike." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "High Pass Filter" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What would we do if we wanted to filter out the lower frequency and isolate the higher one? For that, we would need the opposite of a low-pass filter, which is called, you guessed it, a high-pass filter. We can construct a high-pass filter from a low-pass filter quite easily by flipping the frequency response vertically. That is\n", "\n", "$$H_{high}(f) = 1 - H_{low}(f)$$\n", "\n", "The impulse response of the high-pass filter is the inverse fourier transform of the frequency response. As we have seen before, the fourier transform is a linear operation, so the impulse response of the high-pass is the inverse Fourier transform of the constant 1 minus the impulse response of the low-pass filter.\n", "\n", "$$h_{high}(t) = \\delta(t) - h_{low}(f)$$\n", "\n", "The inverse fourier transform of 1 is $\\delta(t)$, the delta impulse function. In discrete time, $\\delta(t)$ is a function which is 1 at the origin and 0 everywhere else." ] }, { "cell_type": "code", "collapsed": false, "input": [ "delta = zeros(Float32, 2 * sinc_w + 1)\n", "delta[sinc_w + 1] = 1.0\n", "t = [-sinc_w:sinc_w] / sampRate\n", "plot(t, delta)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 35, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 35 }, { "cell_type": "code", "collapsed": false, "input": [ "Delta = abs(rfft(delta))\n", "# set the edges to different numbers so you can clearly see the scale\n", "f = linspace(0, sampRate / 2, sinc_w + 1)\n", "ylim([0.0, 1.1])\n", "plot(f, Delta)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 55, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 55 }, { "cell_type": "markdown", "metadata": {}, "source": [ "So subtracting our low-pass filter kernel from the delta function will give us our high-pass filter." ] }, { "cell_type": "code", "collapsed": false, "input": [ "highp_h = delta - win_sinc_h\n", "plot(t, highp_h)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 44, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 44 }, { "cell_type": "code", "collapsed": false, "input": [ "Highp_H = abs(rfft(highp_h))\n", "plot(f, Highp_H)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 45, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 45 }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we convolved the high-pass filter kernel with the chord, we can isolate the higher frequency." ] }, { "cell_type": "code", "collapsed": false, "input": [ "filtered_x = conv(chord, highp_h)\n", "t = [0:length(filtered_x) - 1] / sampRate\n", "plot(t, filtered_x)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 48, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 48 }, { "cell_type": "code", "collapsed": false, "input": [ "Filtered_X = abs(rfft(filtered_x))\n", "f = linspace(0, sampRate / 2, length(Filtered_X))\n", "plot(f, Filtered_X)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "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", "svg": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n" ], "text": [ "Figure(PyObject )" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 49, "text": [ "1-element Array{Any,1}:\n", " PyObject " ] } ], "prompt_number": 49 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The result of this filter has a lot more distortion than the low-pass filter. This is because our pass band is a lot wider." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Audio Signals" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So now we know what these signals and filters look like, but what do they sound like? To explore this, I decided to find a Creative Commons song from [Jamendo](http://www.jamendo.com/en/) and run it through a high pass and low pass filter.\n", "\n", "The song I decided to use was [Savarnah](http://www.jamendo.com/en/track/887031/savarnah-by-pasqualino-ubaldini-paolo-pavan) by Pasqualino Ubaldini and Paolo Pavan (CC-BY-NC-SA). Here's the original song." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now here is the song put through a low-pass filter with a corner frequency of 440 Hz. You may want to turn your speakers up a bit for this one, since the low-pass filtering muffles the audio quite a bit. But you can hear the low notes (especially on the guitar) get emphasized quite a bit compared to the high notes. Also, the higher harmonics of the notes are filtered out, so the texture of the instruments' sounds (called the timbre in music theory terminology) is changed." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here is the song put through a high-pass filter with a corner frequency of 880 Hz. The higher notes all go through, but now you can barely hear the lower notes. In fact, the low notes sound higher now because you are just hearing the harmonics and not the base note." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] } ], "metadata": {} } ] }