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Conference Paper: A robust quasi-newton adaptive filtering algorithm for impulse noise suppression

TitleA robust quasi-newton adaptive filtering algorithm for impulse noise suppression
Authors
KeywordsElectronics
Issue Date2001
PublisherIEEE.
Citation
Proceedings - Ieee International Symposium On Circuits And Systems, 2001, v. 2, p. II677-II680 How to Cite?
AbstractThis paper studies the problem of robust adaptive filtering in impulse noise environment using the Quasi-Newton (QN) adaptive filtering algorithm. An M-estimate based cost function is minimized instead of the commonly used mean square error (MSE) to suppress the adverse effect of the impulse noise on the filter coefficients. In particular, a new robust quasi-Newton (R-QN) algorithm using the self-scaling variable metric (SSV) method for unconstrained optimization is studied in details. Simulation results show that the R-QN algorithm is more robust to impulse noise in the desired signal than the RLS algorithm and other QN algorithm considered. Its initial convergence speed and tracking ability to sudden system change are also superior to those of the quasi-Newton algorithm proposed in [1].
Persistent Identifierhttp://hdl.handle.net/10722/46256
ISSN
2023 SCImago Journal Rankings: 0.307

 

DC FieldValueLanguage
dc.contributor.authorZou, Yen_HK
dc.contributor.authorChan, SCen_HK
dc.date.accessioned2007-10-30T06:45:54Z-
dc.date.available2007-10-30T06:45:54Z-
dc.date.issued2001en_HK
dc.identifier.citationProceedings - Ieee International Symposium On Circuits And Systems, 2001, v. 2, p. II677-II680en_HK
dc.identifier.issn0271-4310en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46256-
dc.description.abstractThis paper studies the problem of robust adaptive filtering in impulse noise environment using the Quasi-Newton (QN) adaptive filtering algorithm. An M-estimate based cost function is minimized instead of the commonly used mean square error (MSE) to suppress the adverse effect of the impulse noise on the filter coefficients. In particular, a new robust quasi-Newton (R-QN) algorithm using the self-scaling variable metric (SSV) method for unconstrained optimization is studied in details. Simulation results show that the R-QN algorithm is more robust to impulse noise in the desired signal than the RLS algorithm and other QN algorithm considered. Its initial convergence speed and tracking ability to sudden system change are also superior to those of the quasi-Newton algorithm proposed in [1].en_HK
dc.format.extent416483 bytes-
dc.format.extent27162 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofProceedings - IEEE International Symposium on Circuits and Systemsen_HK
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.-
dc.subjectElectronicsen_HK
dc.titleA robust quasi-newton adaptive filtering algorithm for impulse noise suppressionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0271-4302&volume=2&spage=677&epage=680&date=2001&atitle=A+robust+quasi-Newton+adaptive+filtering+algorithm+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/ISCAS.2001.921161en_HK
dc.identifier.scopuseid_2-s2.0-0034999106en_HK
dc.identifier.hkuros60494-
dc.identifier.volume2en_HK
dc.identifier.spageII677en_HK
dc.identifier.epageII680en_HK
dc.identifier.scopusauthoridZou, Y=7402166847en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.issnl0271-4310-

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