Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm

In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Zerguine, A. (author)
مؤلفون آخرون: Aboulnasr, T. (author), unknown (author)
التنسيق: article
منشور في: 2000
الموضوعات:
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/14069/1/14069_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14069/2/14069_2.doc
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author Zerguine, A.
author2 Aboulnasr, T.
unknown
author2_role author
author
author_facet Zerguine, A.
Aboulnasr, T.
unknown
author_role author
dc.creator.none.fl_str_mv Zerguine, A.
Aboulnasr, T.
unknown
dc.date.none.fl_str_mv 2000
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14069/1/14069_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14069/2/14069_2.doc
(2000) Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm. Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar conference, 1.
dc.language.none.fl_str_mv en
en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14069/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. Sufficient and necessary conditions for the convergence of the algorithm are derived. Furthermore, bounds on the step size to ensure convergence of the LMF algorithm are also derived
eu_rights_str_mv openAccess
format article
id KFUPM_04fa31af6a6bb7ea133ea9447c8effa4
identifier_str_mv (2000) Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm. Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar conference, 1.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14069
publishDate 2000
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithmZerguine, A.Aboulnasr, T.unknownComputerIn this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. Sufficient and necessary conditions for the convergence of the algorithm are derived. Furthermore, bounds on the step size to ensure convergence of the LMF algorithm are also derivedIEEE20002020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14069/1/14069_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14069/2/14069_2.doc (2000) Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm. Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar conference, 1. enenhttps://eprints.kfupm.edu.sa/id/eprint/14069/info:eu-repo/semantics/openAccessoai::140692019-11-01T14:04:00Z
spellingShingle Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
Zerguine, A.
Computer
status_str publishedVersion
title Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
title_full Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
title_fullStr Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
title_full_unstemmed Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
title_short Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
title_sort Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14069/1/14069_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14069/2/14069_2.doc