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Article: Fir-myriad hybrid filters for signal processing in impulsive noise environments

TitleFir-myriad hybrid filters for signal processing in impulsive noise environments
Authors
KeywordsAdaptive Algorithms
Backpropagation Algorithms
Fir Filters
Impulse Noise
Neural Networks
Nonlinear Filtering
Issue Date2007
Citation
First International Conference on Communications and Networking in China, ChinaCom '06, 2007 How to Cite?
AbstractA new class of nonlinear filters called FIR-weighted myriad hybrid (FIR-WMyH) filters was introduced. These filters have a combination structure of linear FIR filters and weighted myriad filter, and can efficiently utilize the special strongpoint of two filters. Through the backpropagation algorithm used in the neural networks, we derive a stochastic gradient-based adaptive algorithm for determining optimal FIR-WMyH filters under the mean square error (MSE) criterion. In two impulsive noise models, the robust performance of this adaptive algorithm is demonstrated through the computer simulation results. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/91133
References

 

DC FieldValueLanguage
dc.contributor.authorLin, Ben_HK
dc.contributor.authorZhang, Cen_HK
dc.contributor.authorWang, Xen_HK
dc.contributor.authorGu, Cen_HK
dc.contributor.authorWang, Ben_HK
dc.date.accessioned2010-09-17T10:13:31Z-
dc.date.available2010-09-17T10:13:31Z-
dc.date.issued2007en_HK
dc.identifier.citationFirst International Conference on Communications and Networking in China, ChinaCom '06, 2007en_HK
dc.identifier.urihttp://hdl.handle.net/10722/91133-
dc.description.abstractA new class of nonlinear filters called FIR-weighted myriad hybrid (FIR-WMyH) filters was introduced. These filters have a combination structure of linear FIR filters and weighted myriad filter, and can efficiently utilize the special strongpoint of two filters. Through the backpropagation algorithm used in the neural networks, we derive a stochastic gradient-based adaptive algorithm for determining optimal FIR-WMyH filters under the mean square error (MSE) criterion. In two impulsive noise models, the robust performance of this adaptive algorithm is demonstrated through the computer simulation results. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofFirst International Conference on Communications and Networking in China, ChinaCom '06en_HK
dc.subjectAdaptive Algorithmsen_HK
dc.subjectBackpropagation Algorithmsen_HK
dc.subjectFir Filtersen_HK
dc.subjectImpulse Noiseen_HK
dc.subjectNeural Networksen_HK
dc.subjectNonlinear Filteringen_HK
dc.titleFir-myriad hybrid filters for signal processing in impulsive noise environmentsen_HK
dc.typeArticleen_HK
dc.identifier.emailLin, B:blin@hku.hken_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/CHINACOM.2006.344850en_HK
dc.identifier.scopuseid_2-s2.0-36048971786en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-36048971786&selection=ref&src=s&origin=recordpageen_HK

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