2024 : 11 : 16
Azam Khalili

Azam Khalili

Academic rank: Associate Professor
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Education: PhD.
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Faculty: Technical Engineering
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Research

Title
Tracking Analysis of Maximum Versoria Criterion Based Adaptive Filter
Type
JournalPaper
Keywords
Adaptive filter, non-stationary, performance analysis, tracking, Versoria.
Year
2024
Journal IEEE Access
DOI
Researchers Azam Khalili ، Amir Rastegarnia

Abstract

Recently, maximum Versoria criterion-based adaptive algorithms have been introduced as a new solution for robust adaptive filtering. This paper studies the steady-state tracking analysis of an adaptive filter with maximum Versoria criterion (MVC) in a non-stationary (Markov time-varying) system. Our analysis relies on the energy conservation method. Both Gaussian and general non-Gaussian noise are considered, and for both cases, the closed-form expression for steady-state excess mean square error (EMSE) is derived. Regardless of noise type, unlike the stationary environment, the EMSE curves are not increasing functions of step-size parameter. The validity of the theoretical results is justified via simulation.