Stochastic Model for the LMS Algorithm with Symmetric/Antisymmetric Properties

This paper presents a stochastic model for the least-mean-square algorithm with symmetric/antisymmetric properties (LMS-SAS), operating in a system identification setup with Gaussian input data. Specifically, model expressions are derived to describe the mean weight behavior of the (global and virtu...

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Published inSymmetry (Basel) Vol. 14; no. 9; p. 1908
Main Authors Becker, Augusto Cesar, Kuhn, Eduardo Vinicius, Matsuo, Marcos Vinicius, Benesty, Jacob, Paleologu, Constantin, Dogariu, Laura-Maria, Ciochină, Silviu
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2022
Subjects
Adaptive filters
Algorithms
Expected values
Learning curves
Stochastic models
System identification
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ISSN2073-8994
2073-8994
DOI10.3390/sym14091908

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Summary:This paper presents a stochastic model for the least-mean-square algorithm with symmetric/antisymmetric properties (LMS-SAS), operating in a system identification setup with Gaussian input data. Specifically, model expressions are derived to describe the mean weight behavior of the (global and virtual) adaptive filters, learning curves, and evolution of some correlation-like matrices, which allow predicting the algorithm behavior. Simulation results are shown and discussed, confirming the accuracy of the proposed model for both transient and steady-state phases.
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content type line 14
ISSN:2073-8994
2073-8994
DOI:10.3390/sym14091908