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Article: A new block-exact fast LMS/Newton adaptive filtering algorithm

TitleA new block-exact fast LMS/Newton adaptive filtering algorithm
Authors
KeywordsAdaptive filter
Block exact
Fast least-mean squares (LMS)/Newton algorithm
Issue Date2006
PublisherIEEE.
Citation
IEEE Transactions On Signal Processing, 2006, v. 54 n. 1, p. 374-380 How to Cite?
AbstractThis correspondence proposes a new block-exact fast least-mean squares (LMS)/Newton algorithm for adaptive filtering. It is obtained by exploiting the shifting property of the whitened input of the fast LMS/ Newton algorithm so that a block-exact update can be carried out in the LMS part of the algorithm. The proposed algorithm has significantly less computational complexity than, but exact mathematical equivalence to, the fast LMS/Newton algorithm. Since short block length is allowed, the processing delay introduced is not excessively large as in conventional block filtering generalization. Implementation issues and the experimental results are given to illustrate the principle and efficiency of the proposed algorithm. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/44802
ISSN
2023 Impact Factor: 4.6
2023 SCImago Journal Rankings: 2.520
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZhou, Yen_HK
dc.contributor.authorChan, SCen_HK
dc.contributor.authorHo, KLen_HK
dc.date.accessioned2007-10-30T06:10:32Z-
dc.date.available2007-10-30T06:10:32Z-
dc.date.issued2006en_HK
dc.identifier.citationIEEE Transactions On Signal Processing, 2006, v. 54 n. 1, p. 374-380en_HK
dc.identifier.issn1053-587Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/44802-
dc.description.abstractThis correspondence proposes a new block-exact fast least-mean squares (LMS)/Newton algorithm for adaptive filtering. It is obtained by exploiting the shifting property of the whitened input of the fast LMS/ Newton algorithm so that a block-exact update can be carried out in the LMS part of the algorithm. The proposed algorithm has significantly less computational complexity than, but exact mathematical equivalence to, the fast LMS/Newton algorithm. Since short block length is allowed, the processing delay introduced is not excessively large as in conventional block filtering generalization. Implementation issues and the experimental results are given to illustrate the principle and efficiency of the proposed algorithm. © 2006 IEEE.en_HK
dc.format.extent248980 bytes-
dc.format.extent2800 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Transactions on Signal Processingen_HK
dc.rights©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectAdaptive filteren_HK
dc.subjectBlock exacten_HK
dc.subjectFast least-mean squares (LMS)/Newton algorithmen_HK
dc.titleA new block-exact fast LMS/Newton adaptive filtering algorithmen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1053-587X&volume=54&issue=1&spage=374&epage=380&date=2006&atitle=A+new+block-exact+fast+LMS/Newton+adaptive+filtering+algorithmen_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.emailHo, KL:klho@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.identifier.authorityHo, KL=rp00117en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TSP.2005.861099en_HK
dc.identifier.scopuseid_2-s2.0-30444437771en_HK
dc.identifier.hkuros121268-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-30444437771&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume54en_HK
dc.identifier.issue1en_HK
dc.identifier.spage374en_HK
dc.identifier.epage380en_HK
dc.identifier.isiWOS:000234755600033-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridZhou, Y=8862218900en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridHo, KL=7403581592en_HK
dc.identifier.issnl1053-587X-

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