Signal denoising by piecewise continuous polynomial fitting

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buir.contributor.authorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.citation.epage72en_US
dc.citation.spage69en_US
dc.contributor.authorYıldız, Aykuten_US
dc.contributor.authorArıkan, Orhanen_US
dc.coverage.spatialDiyarbakir, Turkeyen_US
dc.date.accessioned2016-02-08T12:20:30Z
dc.date.available2016-02-08T12:20:30Z
dc.date.issued2010en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 22-24 April 2010en_US
dc.description.abstractPiecewise smooth signal denoising is cast as a non-linear optimization problem in terms of transition boundaries and a parametric smooth signal family. Optimal transition boundaries for a given number of transitions are obtained by using particle swarm optimization. The piecewise smooth section parameters are obtained as the maximum likelihood estimates conditioned on the optimal transition boundaries. The proposed algorithm is extended to the case where the number of transition boundaries are unknown by sequentially increasing number of sections until the residual error is at the level of noise standard deviation. Performance comparison with the state of the art techniques reveals the important advantages of the proposed technique. ©2010 IEEE.en_US
dc.identifier.doi10.1109/SIU.2010.5651446en_US
dc.identifier.urihttp://hdl.handle.net/11693/28432
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2010.5651446en_US
dc.source.title2010 IEEE 18th Signal Processing and Communications Applications Conferenceen_US
dc.subjectMaximum likelihood estimateen_US
dc.subjectNon-linear optimization problemsen_US
dc.subjectOptimal transitionen_US
dc.subjectPerformance comparisonen_US
dc.subjectPiecewise smoothen_US
dc.subjectPiecewise-continuousen_US
dc.subjectPolynomial fittingsen_US
dc.subjectResidual erroren_US
dc.subjectSignal denoisingen_US
dc.subjectStandard deviationen_US
dc.subjectState of the arten_US
dc.subjectTransition boundariesen_US
dc.subjectAlgorithmsen_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectNoise pollution controlen_US
dc.subjectParticle swarm optimization (PSO)en_US
dc.subjectSignal processingen_US
dc.titleSignal denoising by piecewise continuous polynomial fittingen_US
dc.title.alternativeParçali sürekli sinyallerde parametrik modelleme ile gürültü bastirimien_US
dc.typeConference Paperen_US

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