Comparison of Wavelets for Classification of Cognitive EEG Signals

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dc.authoridERALDEMIR, SERVER GOKSEL/0000-0003-0835-2601
dc.contributor.authorEraldemir, S. Goksel
dc.contributor.authorYildirim, Esen
dc.date.accessioned2024-09-18T20:59:13Z
dc.date.available2024-09-18T20:59:13Z
dc.date.issued2015
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractIn this work, different wavelet types, that have been frequently used in EEG signal analysis and classification, are compared for cognitive EEG classification. EEG signals are collected from 18 healthy subjects during math processing and simple text reading. Symlet, coiflet and bior wavelet types are used for feature extraction and classification performances of BayesNet and J48 classifiers are compared. The best true positive rate of 90.6% is obtained using Boir 2.4 wavelet type with J48 classifier.en_US
dc.description.sponsorshipDept Comp Engn & Elect & Elect Engn,Elect & Elect Engn,Bilkent Univen_US
dc.identifier.endpage1384en_US
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-84939142408en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1381en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12483/12462
dc.identifier.wosWOS:000380500900326en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2015 23rd Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSymleten_US
dc.subjectCoifleten_US
dc.subjectBiorthogonalen_US
dc.subjectDiscrete Wavelet Transformen_US
dc.subjectEEG Classificationen_US
dc.titleComparison of Wavelets for Classification of Cognitive EEG Signalsen_US
dc.typeConference Objecten_US

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