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Signal Stationarity Estimation with Matlab

version 1.3.0 (145 KB) by Hristo Zhivomirov
Wide-sense stationarity estimation of a signal using a novel method.

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Updated 29 Apr 2021

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The present code is a Matlab function for wide-sense stationarity estimation of a signal using a novel method. According the theory, the objects of estimation are: the mean, the variance and the autocovariance of the signal under test. The three parameters must be time-independent in order to mark a signal as a non-stationary one.
The function provides a computation of four Boolean flags for:
1) overall wide-sense stationarity i.e., simultaneously stationarity about mean, variance and autocovariance;
2) stationarity about the mean (or linear trend);
3) stationarity about the variance (and hence about the RMS-value);
4) time-invariance of the autocovariance (and hence of the autocorrelation and PSD).

A few examples are given in order to clarify the usage of the function. For convenience, the input and output arguments are given in the beginning of the function.

The code is based on the theory described in:

[1] H. Zhivomirov, I. Nedelchev. A Method for Signal Stationarity Estimation. Romanian Journal of Acoustics and Vibration, ISSN: 1584-7284, Vol. XVII, No. 2, pp. 149-155, 2020. (http://rjav.sra.ro/index.php/rjav/article/view/178/103).

Cite As

H. Zhivomirov, I. Nedelchev. A Method for Signal Stationarity Estimation. Romanian Journal of Acoustics and Vibration, ISSN: 1584-7284, Vol. XVII, No. 2, pp. 149-155, 2020. (http://rjav.sra.ro/index.php/rjav/article/view/178/103).

Hristo Zhivomirov (2021). Signal Stationarity Estimation with Matlab (https://www.mathworks.com/matlabcentral/fileexchange/75118-signal-stationarity-estimation-with-matlab), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (3)

Peng

Hristo Zhivomirov

Hi Med! Thank you very much about your interest on my submission and for your comment. I think the "stationary semaphore" which I proposed is quite informative about the stationarity of the signal. The "stationary semaphore" mimics the street traffic light, with three light sections – for the mean stationary flag, for the variance stationary flag and one for the autocovariance. The signal is determined as WSS if all flags are raised i.e., if there is full “green light” on the semaphore. When the signal under test is highly non-stationary, all three sections are in red.

Kind regards,
Hristo

Med Aymane Ahajjam

Thank you. Yet, I think you need to change the titles of the subfigures to reflect degrees of stationarity no? Because in the case signals TS1 - 3 all three boolean parameters are equal to 1.

MATLAB Release Compatibility
Created with R2017b
Compatible with any release
Platform Compatibility
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