PINK_NOISE
Samples of a Pink Noise Signal


PINK_NOISE is a MATLAB library which can generate random values taken from an approximate pink noise signal obeying a 1/f power law.

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Languages:

PINK_NOISE is available in a C version and a C++ version and a FORTRAN77 version and a FORTRAN90 version and a MATLAB version.

Related Data and Programs:

BROWNIAN_MOTION_SIMULATION, a MATLAB program which simulates Brownian motion in an M-dimensional region.

CNOISE, a MATLAB library which generates samples of noise obeying a 1/f^alpha power law, by Miroslav Stoyanov.

COLORED_NOISE, a MATLAB library which generates samples of noise obeying a 1/f^alpha power law.

CORRELATION, a MATLAB library which contains examples of statistical correlation functions.

NORMAL, a MATLAB library which computes elements of a sequence of pseudorandom normally distributed values.

STOCHASTIC_RK, a MATLAB library which applies a Runge-Kutta scheme to a stochastic differential equation.

UNIFORM, a MATLAB library which computes elements of a uniform pseudorandom sequence.

Reference:

  1. Martin Gardner,
    White and brown music, fractal curves and one-over-f fluctuations,
    Scientific American,
    Volume 238, Number 4, April 1978, pages 16-32.
  2. Jeremy Kasdin,
    Discrete Simulation of Colored Noise and Stochastic Processes and 1/f^a Power Law Noise Generation,
    Proceedings of the IEEE,
    Volume 83, Number 5, 1995, pages 802-827.
  3. Edoardo Milotti,
    1/f noise: a pedagogical review,
    arXiv:physics/0204033.
  4. Sophocles Orfanidis,
    Introduction to Signal Processing,
    Prentice-Hall, 1995,
    ISBN: 0-13-209172-0,
    LC: TK5102.5.O246.
  5. William Press,
    Flicker Noises in Astronomy and Elsewhere,
    Comments on Astrophysics,
    Volume 7, Number 4, 1978, pages 103-119.
  6. Miroslav Stoyanov, Max Gunzburger, John Burkardt,
    Pink Noise, 1/f^alpha Noise, and Their Effect on Solutions of Differential Equations,
    International Journal for Uncertainty Quantification,
    Volume 1, Number 3, pages 257-278, 2011.

Source Code:

Examples and Tests:

You can go up one level to the MATLAB source codes.


Last revised on 20 June 2010.