Tracking Analysis of Maximum Versoria Criterion Based Adaptive Filter

Azam Khalili, Amir Rastegarnia, Ali Farzamnia, Saeid Sanei, Thamer A.H. Alghamdi

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number10445217
Pages (from-to)30747-30753
Number of pages7
JournalIEEE Access
Volume12
Early online date26 Feb 2024
DOIs
Publication statusPublished - 1 Mar 2024
Externally publishedYes

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