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Conference Paper: Multi-resolution analysis of non-uniform data with jump discontinuities and impulsive noise using robust local polynomial regression

TitleMulti-resolution analysis of non-uniform data with jump discontinuities and impulsive noise using robust local polynomial regression
Authors
KeywordsEngineering
Electrical engineering
Issue Date2004
PublisherIEEE.
Citation
Icassp, Ieee International Conference On Acoustics, Speech And Signal Processing - Proceedings, 2004, v. 2, p. II769-II772 How to Cite?
AbstractThis paper proposes a new method for performing multiresolution analysis (MRA) of non-uniform data with jump discontinuities and impulsive noise using robust M-estimator-based local polynomial regression (LPR). The basic idea is to interpolate the smoothed estimate, after performing the robust LPR, on a uniform grid in order to perform the MRA using the ordinary wavelet transform. Simulation results show that the new approach performs better than traditional LS-based LPR in preserving jump discontinuities and suppressing isolated impulses when the intersection confident intervals (ICI) bandwidth selection is employed.
Persistent Identifierhttp://hdl.handle.net/10722/46424
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChan, SCen_HK
dc.contributor.authorZhang, Zen_HK
dc.date.accessioned2007-10-30T06:49:34Z-
dc.date.available2007-10-30T06:49:34Z-
dc.date.issued2004en_HK
dc.identifier.citationIcassp, Ieee International Conference On Acoustics, Speech And Signal Processing - Proceedings, 2004, v. 2, p. II769-II772en_HK
dc.identifier.issn1520-6149en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46424-
dc.description.abstractThis paper proposes a new method for performing multiresolution analysis (MRA) of non-uniform data with jump discontinuities and impulsive noise using robust M-estimator-based local polynomial regression (LPR). The basic idea is to interpolate the smoothed estimate, after performing the robust LPR, on a uniform grid in order to perform the MRA using the ordinary wavelet transform. Simulation results show that the new approach performs better than traditional LS-based LPR in preserving jump discontinuities and suppressing isolated impulses when the intersection confident intervals (ICI) bandwidth selection is employed.en_HK
dc.format.extent330745 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.rights©2004 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.subjectEngineeringen_HK
dc.subjectElectrical engineeringen_HK
dc.titleMulti-resolution analysis of non-uniform data with jump discontinuities and impulsive noise using robust local polynomial regressionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1520-6149&volume=2&spage=769&epage=772&date=2004&atitle=Multi-resolution+analysis+of+non-uniform+data+with+jump+discontinuities+and+impulsive+noise+using+robust+local+polynomial+regressionen_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.emailZhang, Z:zgzhang@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.identifier.authorityZhang, Z=rp01565en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICASSP.2004.1326371en_HK
dc.identifier.scopuseid_2-s2.0-4644252568en_HK
dc.identifier.hkuros90048-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-4644252568&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2en_HK
dc.identifier.spageII769en_HK
dc.identifier.epageII772en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridZhang, Z=8597618700en_HK
dc.identifier.issnl1520-6149-

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