One-point random process generation

version 1.0 (57.5 KB) by E. Cheynet
Minimalist Matlab implementation of a random process generation in one point using the spectral method

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Updated 11 Jun 2020

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One-point random process generation

Minimalist Matlab implementation of a random process generation in one point

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Summary

A stationary Gaussian random process is generated using the spectral method. This means that the function requires only two inputs: the target power spectral density (PSD) and the associated frequency vector.

Content

The present submission contains:

  • The function randomProcess.m, which generates the (random) time series associated with a target PSD
  • An example file Documentation.mlx, which illustrates the generation of the random process using the case of atmospheric turbulence
  • The function getSamplingPara.m, which computes the target frequency vector and the associated time vector.

Any question, suggestion or comment is welcome.

Example

Comparison between the target and estimated power-spectral density for turbulence data

Cite As

Cheynet, E. Minimalist Matlab Implementation of a Random Process Generation in One Point. Zenodo, 2020, doi:10.5281/ZENODO.3890406.

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MATLAB Release Compatibility
Created with R2019b
Compatible with R2018a and later releases
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired: Stationarity test

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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.