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Article: Adaptive weighted FIR-Myriad hybrid filter algorithm

TitleAdaptive weighted FIR-Myriad hybrid filter algorithm
Authors
Lin, BWang, X-DZhang, C-YXia, Z-ZWang, B-S
KeywordsBack Propagation Algorithm
Impulsive Noise
Minimum Square Error Criterion
Nonlinear Filter
Weighted Myriad Filter
Issue Date2006
Citation
Dianbo Kexue Xuebao/Chinese Journal of Radio Science, 2006, v. 21 n. 5, p. 788-790+801 How to Cite?
AbstractA class of nonlinear filters called as the weighted FIR-Myriad hybrid (FIR-WMyH) filters were proposed. These filters can overcome the disadvantages of FIR filter and weighted Myriad filter. Through the back-propagation algorithm used in neural networks, a stochastic gradient-based adaptive algorithm for determining optimal FIR-WMyH filters under the mean square error (MSE) criterion is derived. In the case of the stable distributed impulsive noise model, the good performance of this adaptive algorithm is demonstrated through the computer simulation results.
Persistent Identifierhttp://hdl.handle.net/10722/91096
ISSN
1005-0388
2023 SCImago Journal Rankings: 0.189
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorLin, Ben_HK
dc.contributor.authorWang, X-Den_HK
dc.contributor.authorZhang, C-Yen_HK
dc.contributor.authorXia, Z-Zen_HK
dc.contributor.authorWang, B-Sen_HK
dc.date.accessioned2010-09-17T10:12:58Z-
dc.date.available2010-09-17T10:12:58Z-
dc.date.issued2006en_HK
dc.identifier.citationDianbo Kexue Xuebao/Chinese Journal of Radio Science, 2006, v. 21 n. 5, p. 788-790+801en_HK
dc.identifier.issn1005-0388en_HK
dc.identifier.urihttp://hdl.handle.net/10722/91096-
dc.description.abstractA class of nonlinear filters called as the weighted FIR-Myriad hybrid (FIR-WMyH) filters were proposed. These filters can overcome the disadvantages of FIR filter and weighted Myriad filter. Through the back-propagation algorithm used in neural networks, a stochastic gradient-based adaptive algorithm for determining optimal FIR-WMyH filters under the mean square error (MSE) criterion is derived. In the case of the stable distributed impulsive noise model, the good performance of this adaptive algorithm is demonstrated through the computer simulation results.en_HK
dc.languageengen_HK
dc.relation.ispartofDianbo Kexue Xuebao/Chinese Journal of Radio Scienceen_HK
dc.subjectBack Propagation Algorithmen_HK
dc.subjectImpulsive Noiseen_HK
dc.subjectMinimum Square Error Criterionen_HK
dc.subjectNonlinear Filteren_HK
dc.subjectWeighted Myriad Filteren_HK
dc.titleAdaptive weighted FIR-Myriad hybrid filter algorithmen_HK
dc.typeArticleen_HK
dc.identifier.emailLin, B:blin@hku.hken_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-33845888033en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33845888033&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume21en_HK
dc.identifier.issue5en_HK
dc.identifier.spage788en_HK
dc.identifier.epage790+801en_HK
dc.identifier.issnl1005-0388-

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