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Conference Paper: A Huber recursive least squares adaptive lattice filter for impulse noise suppression

TitleA Huber recursive least squares adaptive lattice filter for impulse noise suppression
Authors
KeywordsEngineering
Electrical engineering
Issue Date2001
PublisherIEEE.
Citation
Icassp, Ieee International Conference On Acoustics, Speech And Signal Processing - Proceedings, 2001, v. 6, p. 3769-3772 How to Cite?
AbstractThis paper proposes a new adaptive filtering algorithm called the Huber Prior Error-Feedback Least Squares Lattice (H-PEF-LSL) algorithm for robust adaptive filtering in impulse noise environment. It minimizes a modified Huber M-estimator based cost function, instead of the least squares cost function. In addition, the simple modified Huber M-estimate cost function also allows us to perform the time and order recursive updates in the conventional PEF-LSL algorithm so that the complexity can be significantly reduced to O(M), where M is the length of the adaptive filter. The new algorithm can also be viewed as an efficient implementation of the recursive least M-estimate (RLM) algorithm recently proposed by the authors [1], which has a complexity of O(M 2). Simulation results show that the proposed H-PEF-LSL algorithm is more robust than the conventional PEF-LSL algorithm in suppressing the adverse influence of the impulses at the input and desired signals with small additional computational cost.
Persistent Identifierhttp://hdl.handle.net/10722/46257
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorZou, Yen_HK
dc.contributor.authorChan, SCen_HK
dc.date.accessioned2007-10-30T06:45:55Z-
dc.date.available2007-10-30T06:45:55Z-
dc.date.issued2001en_HK
dc.identifier.citationIcassp, Ieee International Conference On Acoustics, Speech And Signal Processing - Proceedings, 2001, v. 6, p. 3769-3772en_HK
dc.identifier.issn0736-7791en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46257-
dc.description.abstractThis paper proposes a new adaptive filtering algorithm called the Huber Prior Error-Feedback Least Squares Lattice (H-PEF-LSL) algorithm for robust adaptive filtering in impulse noise environment. It minimizes a modified Huber M-estimator based cost function, instead of the least squares cost function. In addition, the simple modified Huber M-estimate cost function also allows us to perform the time and order recursive updates in the conventional PEF-LSL algorithm so that the complexity can be significantly reduced to O(M), where M is the length of the adaptive filter. The new algorithm can also be viewed as an efficient implementation of the recursive least M-estimate (RLM) algorithm recently proposed by the authors [1], which has a complexity of O(M 2). Simulation results show that the proposed H-PEF-LSL algorithm is more robust than the conventional PEF-LSL algorithm in suppressing the adverse influence of the impulses at the input and desired signals with small additional computational cost.en_HK
dc.format.extent439932 bytes-
dc.format.extent27162 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedingsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2001 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.en_HK
dc.subjectEngineeringen_HK
dc.subjectElectrical engineeringen_HK
dc.titleA Huber recursive least squares adaptive lattice filter for impulse noise suppressionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1520-6149&volume=6&spage=3769&epage=3772&date=2001&atitle=A+Huber+recursive+least+squares+adaptive+lattice+filter+for+impulse+noise+suppressionen_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICASSP.2001.940663en_HK
dc.identifier.scopuseid_2-s2.0-0034848197en_HK
dc.identifier.hkuros60496-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034848197&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.spage3769en_HK
dc.identifier.epage3772en_HK
dc.identifier.scopusauthoridZou, Y=7402166847en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK

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