Robust adaptive filtering algorithms for α-stable random processes

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buir.contributor.authorArıkan, Orhan
buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage202en_US
dc.citation.issueNumber2en_US
dc.citation.spage198en_US
dc.citation.volumeNumber46en_US
dc.contributor.authorAydin, G.en_US
dc.contributor.authorArıkan, Orhanen_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2016-02-08T10:41:56Z
dc.date.available2016-02-08T10:41:56Z
dc.date.issued1999-02en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractA new class of algorithms based on the fractional lower order statistics is proposed for finite-impulse response adaptive filtering in the presence of α-stable processes. It is shown that the normalized least mean p-norm (NLMP) and Douglas' family of normalized least mean square algorithms are special cases of the proposed class of algorithms. A convergence proof for the new algorithm is given by showing that it performs a descent-type update of the NLMP cost function. Simulation studies indicate that the proposed algorithms provide superior performance in impulsive noise environments compared to the existing approaches.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:41:56Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1999en
dc.identifier.doi10.1109/82.752953en_US
dc.identifier.issn1057-7130
dc.identifier.urihttp://hdl.handle.net/11693/25271
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/82.752953en_US
dc.source.titleIEEE Transactions on Circuits and Systems II : Analog and Digital Signal Processingen_US
dc.subjectAdaptive filteringen_US
dc.subjectFIR filtersen_US
dc.subjectMathematical modelsen_US
dc.subjectProbability density functionen_US
dc.subjectRandom processesen_US
dc.subjectSpurious signal noiseen_US
dc.subjectStabilityen_US
dc.subjectStatistical methodsen_US
dc.subjectAlpha stable random processesen_US
dc.subjectFinite impulse response adaptive filteringen_US
dc.subjectImpulsive signalsen_US
dc.subjectLeast mean square algorithmsen_US
dc.subjectNormalized least mean p normen_US
dc.subjectAdaptive algorithmsen_US
dc.titleRobust adaptive filtering algorithms for α-stable random processesen_US
dc.typeArticleen_US

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