One-point random process generation

Version 1.1 (363 KB) by E. Cheynet
Minimalist Matlab implementation of a random process generation in one point using the spectral method
224 Downloads
Updated Mon, 30 Jan 2023 14:23:18 +0000

One-point random process generation

Minimalist Matlab implementation of a random process generation in one point

View One-point random process generation on File Exchange Buy Me A Coffee

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.

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

Inspired: Stationarity test

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.1

See release notes for this release on GitHub: https://github.com/ECheynet/randomProcess/releases/tag/v1.1

1.0

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.