Big data signal processing using boosted RLS algorithm

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dc.citation.epage1092en_US
dc.citation.spage1089en_US
dc.contributor.authorCivek, Burak Cevaten_US
dc.contributor.authorKari, Dariushen_US
dc.contributor.authorDelibalta, İ.en_US
dc.contributor.authorKozat, Süleyman Serdaren_US
dc.coverage.spatialZonguldak, Turkeyen_US
dc.date.accessioned2018-04-12T11:48:36Z
dc.date.available2018-04-12T11:48:36Z
dc.date.issued2016en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 16-19 May 2016en_US
dc.descriptionConference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016en_US
dc.description.abstractWe propose an efficient method for the high dimensional data regression. To this end, we use a least mean squares (LMS) filter followed by a recursive least squares (RLS) filter and combine them via boosting notion extensively used in machine learning literature. Moreover, we provide a novel approach where the RLS filter is updated randomly in order to reduce the computational complexity while not giving up more on the performance. In the proposed algorithm, after the LMS filter produces an estimate, depending on the error made on this step, the algorithm decides whether or not updating the RLS filter. Since we avoid updating the RLS filter for all data sequence, the computational complexity is significantly reduced. Error performance and the computation time of our algorithm is demonstrated for a highly realistic scenario.en_US
dc.identifier.doi10.1109/SIU.2016.7495933en_US
dc.identifier.urihttp://hdl.handle.net/11693/37706
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2016.7495933en_US
dc.source.titleProceedings of the IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016en_US
dc.subjectBig dataen_US
dc.subjectBoostingen_US
dc.subjectLinear filteren_US
dc.subjectLMSen_US
dc.subjectRLSen_US
dc.titleBig data signal processing using boosted RLS algorithmen_US
dc.title.alternativeArttırmalı özyinelemeli en küçük karesel hata algoritması kullanarak büyük veri sinyal işlemesien_US
dc.typeConference Paperen_US

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