k-Wave Toolbox

filterTimeSeries

Filter signal using the Kaiser windowing method

Syntax

filtered_signal = filterTimeSeries(kgrid, medium, signal)
filtered_signal = filterTimeSeries(kgrid, medium, signal, ...)

Description

filterTimeSeries filters an input time domain signal using a low pass filter applied by applyFilter with a specified cut-off frequency, stop-band attenuation, and transition bandwidth. It uses the Kaiser Windowing method to design the FIR filter, which can be implemented as either a zero phase or linear phase filter. The cutoff frequency is defined by a minimum number of temporal points per wavelength. A smoothing ramp can also be applied to the beginning of the signal to reduce high frequency transients.

Inputs

`kgrid`	k-Wave grid structure returned by makeGrid
`medium`	k-Wave medium structure
`signal`	the time domain signal to filter

Optional Inputs

Optional 'string', value pairs that may be used to modify the default computational settings.

Input	Valid Settings	Default	Description
`'PlotSignals'`	(boolean scalar)	`false`	Boolean controlling whether the time signal is displayed before and after filtering.
`'PlotSpectrums'`	(boolean scalar)	`false`	Boolean controlling whether the amplitude spectrum is displayed before and after filtering.
`'PPW'`	(integer numeric scalar)	`3`	The number of points per wavelength used to compute the filter cutoff frequency (setting to 0 turns of the filtering).
`'RampPPW'`	(integer numeric scalar)	`0`	The number of points per wavelength used to compute the length of the cosine start-up ramp (setting to 0 turns off the start-up ramp).
`'StopBandAtten'`	(numeric scalar)	`60`	Attenuation in decibels in the filter stop band.
`'TransitionWidth'`	(numeric scalar)	`0.1`	Size of the transition relative to the temporal sampling frequency.
`'ZeroPhase'`	(boolean scalar)	`false`	Boolean controlling whether a causal or zero phase filter is applied.

Outputs

filtered_signal

the filtered time signal