Boosted LMS-based piecewise linear adaptive filters

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dc.citation.epage1597en_US
dc.citation.spage1593en_US
dc.contributor.authorKari, Dariushen_US
dc.contributor.authorMarivani, Imanen_US
dc.contributor.authorDelibalta, İ.en_US
dc.contributor.authorKozat, Süleyman Serdaren_US
dc.coverage.spatialBudapest, Hungaryen_US
dc.date.accessioned2018-04-12T11:49:43Z
dc.date.available2018-04-12T11:49:43Z
dc.date.issued2016en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 29 August-2 September 2016en_US
dc.descriptionConference Name: 24th European Signal Processing Conference, EUSIPCO 2016en_US
dc.description.abstractWe introduce the boosting notion extensively used in different machine learning applications to adaptive signal processing literature and implement several different adaptive filtering algorithms. In this framework, we have several adaptive constituent filters that run in parallel. For each newly received input vector and observation pair, each filter adapts itself based on the performance of the other adaptive filters in the mixture on this current data pair. These relative updates provide the boosting effect such that the filters in the mixture learn a different attribute of the data providing diversity. The outputs of these constituent filters are then combined using adaptive mixture approaches. We provide the computational complexity bounds for the boosted adaptive filters. The introduced methods demonstrate improvement in the performances of conventional adaptive filtering algorithms due to the boosting effect.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T11:49:43Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2016en
dc.identifier.doi10.1109/EUSIPCO.2016.7760517en_US
dc.identifier.issn2219-5491en_US
dc.identifier.urihttp://hdl.handle.net/11693/37741
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/EUSIPCO.2016.7760517en_US
dc.source.titleProceedings of the 24th European Signal Processing Conference, EUSIPCO 2016en_US
dc.subjectAdaptive boostingen_US
dc.subjectAdaptive filteringen_US
dc.subjectArtificial intelligenceen_US
dc.subjectBandpass filtersen_US
dc.subjectLearning systemsen_US
dc.subjectPiecewise linear techniquesen_US
dc.subjectSignal filtering and predictionen_US
dc.subjectAdaptive filtering algorithmsen_US
dc.subjectAdaptive signal processingen_US
dc.subjectBoosting effectsen_US
dc.subjectInput vectoren_US
dc.subjectMachine learning applicationsen_US
dc.subjectPiecewise linearen_US
dc.subjectAdaptive filtersen_US
dc.titleBoosted LMS-based piecewise linear adaptive filtersen_US
dc.typeConference Paperen_US

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