Cover Image

Tracking analysis of maximum versoria criterion based adaptive filter

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Azam Khalili, Amir Rastegarnia, Ali Farzamnia, Saeid Sanei, Thamer a. H. Alghamdi
Format: Article
Language:English
English
Published: IEEE 2024
Subjects:
QA75-76.95 Calculating machines
TK7800-8360 Electronics
Online Access:https://eprints.ums.edu.my/id/eprint/42124/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/42124/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/42124/
https://doi.org/10.1109/ACCESS.2024.3370471
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ums.eprints.42124
record_format eprints
spelling my.ums.eprints.421242024-12-06T05:13:31Z https://eprints.ums.edu.my/id/eprint/42124/ Tracking analysis of maximum versoria criterion based adaptive filter Azam Khalili Amir Rastegarnia Ali Farzamnia Saeid Sanei Thamer a. H. Alghamdi QA75-76.95 Calculating machines TK7800-8360 Electronics 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. IEEE 2024 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/42124/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/42124/2/FULL%20TEXT.pdf Azam Khalili and Amir Rastegarnia and Ali Farzamnia and Saeid Sanei and Thamer a. H. Alghamdi (2024) Tracking analysis of maximum versoria criterion based adaptive filter. IEEE Access, 12. pp. 1-7. ISSN 2169-3536 https://doi.org/10.1109/ACCESS.2024.3370471
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA75-76.95 Calculating machines
TK7800-8360 Electronics
spellingShingle QA75-76.95 Calculating machines
TK7800-8360 Electronics
Azam Khalili
Amir Rastegarnia
Ali Farzamnia
Saeid Sanei
Thamer a. H. Alghamdi
Tracking analysis of maximum versoria criterion based adaptive filter
description 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.
format Article
author Azam Khalili
Amir Rastegarnia
Ali Farzamnia
Saeid Sanei
Thamer a. H. Alghamdi
author_facet Azam Khalili
Amir Rastegarnia
Ali Farzamnia
Saeid Sanei
Thamer a. H. Alghamdi
author_sort Azam Khalili
title Tracking analysis of maximum versoria criterion based adaptive filter
title_short Tracking analysis of maximum versoria criterion based adaptive filter
title_full Tracking analysis of maximum versoria criterion based adaptive filter
title_fullStr Tracking analysis of maximum versoria criterion based adaptive filter
title_full_unstemmed Tracking analysis of maximum versoria criterion based adaptive filter
title_sort tracking analysis of maximum versoria criterion based adaptive filter
publisher IEEE
publishDate 2024
url https://eprints.ums.edu.my/id/eprint/42124/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/42124/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/42124/
https://doi.org/10.1109/ACCESS.2024.3370471
_version_ 1817843859213778944
score 13.23648

Similar Items