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Conference Paper: A robust M-estimate adaptive equaliser for impulse noise suppression

TitleA robust M-estimate adaptive equaliser for impulse noise suppression
Authors
KeywordsTransportation
Automobiles
Issue Date1999
PublisherIEEE.
Citation
The 49th IEEE VTS Vehicular Technology Conference, Houston, TX., 16-20 May 1999. In IEEEVTS Vehicular Technology Conference. Proceedings, 1999, v. 3, p. 2393-2397 How to Cite?
AbstractIn this paper, a FIR adaptive equaliser for impulse noise suppression is proposed. It is based on the minimization of an M-estimate objective function which has the ability to ignore or down-weight a large error signal when it exceeds certain thresholds. An advantage of the proposed method is that its solution is governed by a system of linear equations, called the M-estimate normal equation. Therefore, traditional fast algorithms like the recursive least squares algorithm can be applied. Using a robust estimation of the thresholds and the recursive least square algorithm, an M-estimate RLS (M-RLS) algorithm is developed. Simulation results show that the proposed algorithm has better convergence performance than the N-RLS and MN-LMS algorithms when the input signal of the equaliser is corrupted by individually or consecutive impulse noises. It also shares the low steady state error of the traditional RLS algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/46117
ISSN

 

DC FieldValueLanguage
dc.contributor.authorZou, Yen_HK
dc.contributor.authorChan, SCen_HK
dc.contributor.authorNg, TSen_HK
dc.date.accessioned2007-10-30T06:42:54Z-
dc.date.available2007-10-30T06:42:54Z-
dc.date.issued1999en_HK
dc.identifier.citationThe 49th IEEE VTS Vehicular Technology Conference, Houston, TX., 16-20 May 1999. In IEEEVTS Vehicular Technology Conference. Proceedings, 1999, v. 3, p. 2393-2397en_HK
dc.identifier.issn1550-2252en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46117-
dc.description.abstractIn this paper, a FIR adaptive equaliser for impulse noise suppression is proposed. It is based on the minimization of an M-estimate objective function which has the ability to ignore or down-weight a large error signal when it exceeds certain thresholds. An advantage of the proposed method is that its solution is governed by a system of linear equations, called the M-estimate normal equation. Therefore, traditional fast algorithms like the recursive least squares algorithm can be applied. Using a robust estimation of the thresholds and the recursive least square algorithm, an M-estimate RLS (M-RLS) algorithm is developed. Simulation results show that the proposed algorithm has better convergence performance than the N-RLS and MN-LMS algorithms when the input signal of the equaliser is corrupted by individually or consecutive impulse noises. It also shares the low steady state error of the traditional RLS algorithm.en_HK
dc.format.extent474073 bytes-
dc.format.extent27162 bytes-
dc.format.extent21012 bytes-
dc.format.extent21377 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEEVTS Vehicular Technology Conference Proceedings-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©1999 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.subjectTransportationen_HK
dc.subjectAutomobilesen_HK
dc.titleA robust M-estimate adaptive equaliser for impulse noise suppressionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1550-2252&volume=3&spage=2393&epage=2397&date=1999&atitle=A+robust+M-estimate+adaptive+equaliser+for+impulse+noise+suppressionen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/VETEC.1999.778501en_HK
dc.identifier.hkuros45103-
dc.identifier.volume3-
dc.identifier.spage2393-
dc.identifier.epage2397-

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