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Conference Paper: Transform domain approximate QR-LS adaptive filtering algorithm

TitleTransform domain approximate QR-LS adaptive filtering algorithm
Authors
Issue Date2003
Citation
Proceedings - Ieee International Symposium On Circuits And Systems, 2003, v. 4, p. IV373-IV376 How to Cite?
AbstractAn improved approximate QR-least squares (A-QR-LS) algorithm, called the transform domain A-QR-LS (TA-QR-LS) algorithm, is introduced. The input signal vector is approximately decorrelated by some unitary transformations before applying the A-QR-LS, which is shown to improve considerably the convergence speed of the A-QR-LS algorithm recently proposed by Liu [4]. Further, it is possible to reduce the arithmetic complexities (O(N)) of the A-QR-LS, and TA-QR-LS algorithms by using Givens rotations instead of the Householder transformation. Simulation results show that the proposed TA-QR-LS algorithm is a good alternative to the conventional recursive least squares (RLS) algorithm in adaptive filtering applications involving multiple channels, acoustic modeling, and fast parameter variations.
Persistent Identifierhttp://hdl.handle.net/10722/158406
ISSN
2023 SCImago Journal Rankings: 0.307
References

 

DC FieldValueLanguage
dc.contributor.authorYang, XXen_US
dc.contributor.authorChan, SCen_US
dc.date.accessioned2012-08-08T08:59:29Z-
dc.date.available2012-08-08T08:59:29Z-
dc.date.issued2003en_US
dc.identifier.citationProceedings - Ieee International Symposium On Circuits And Systems, 2003, v. 4, p. IV373-IV376en_US
dc.identifier.issn0271-4310en_US
dc.identifier.urihttp://hdl.handle.net/10722/158406-
dc.description.abstractAn improved approximate QR-least squares (A-QR-LS) algorithm, called the transform domain A-QR-LS (TA-QR-LS) algorithm, is introduced. The input signal vector is approximately decorrelated by some unitary transformations before applying the A-QR-LS, which is shown to improve considerably the convergence speed of the A-QR-LS algorithm recently proposed by Liu [4]. Further, it is possible to reduce the arithmetic complexities (O(N)) of the A-QR-LS, and TA-QR-LS algorithms by using Givens rotations instead of the Householder transformation. Simulation results show that the proposed TA-QR-LS algorithm is a good alternative to the conventional recursive least squares (RLS) algorithm in adaptive filtering applications involving multiple channels, acoustic modeling, and fast parameter variations.en_US
dc.languageengen_US
dc.relation.ispartofProceedings - IEEE International Symposium on Circuits and Systemsen_US
dc.titleTransform domain approximate QR-LS adaptive filtering algorithmen_US
dc.typeConference_Paperen_US
dc.identifier.emailChan, SC:scchan@eee.hku.hken_US
dc.identifier.authorityChan, SC=rp00094en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-17744408205en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-17744408205&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume4en_US
dc.identifier.spageIV373en_US
dc.identifier.epageIV376en_US
dc.identifier.scopusauthoridYang, XX=7406506103en_US
dc.identifier.scopusauthoridChan, SC=13310287100en_US
dc.identifier.issnl0271-4310-

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