Separation of EEG signals by using independent component analysis

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dc.authorscopusid23973331200
dc.authorscopusid6603490446
dc.authorscopusid55293597800
dc.contributor.authorSezgin N.
dc.contributor.authorTa?luk M.E.
dc.contributor.authorTekin R.
dc.date.accessioned2024-08-04T20:04:00Z
dc.date.available2024-08-04T20:04:00Z
dc.date.issued2012
dc.departmentİnönü Üniversitesien_US
dc.description2012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786en_US
dc.description.abstractIndependent Component Analysis (ICA) is a statistical method used for separating nongaussian independent components of a mixture signal. In this study, by separating the signal into its possible independent components, the simplification and comprehension of analysis of EEG signals was aimed. Through such an analysis it was thought that early diagnosis of some neurological disease such as epilepsy, parkinson's disease, sleep disorders as well as information regarding the location and size of problematic zone may become possible. © 2012 IEEE.en_US
dc.identifier.doi10.1109/SIU.2012.6204677
dc.identifier.isbn9781467300568
dc.identifier.scopus2-s2.0-84863449353en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2012.6204677
dc.identifier.urihttps://hdl.handle.net/11616/92275
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEEGen_US
dc.subjectFastICAen_US
dc.subjectIndependent component analysisen_US
dc.subjectKurtosisen_US
dc.titleSeparation of EEG signals by using independent component analysisen_US
dc.title.alternativeEEG ïşaretleri?ni?n ba?imsiz bi?leşen anali?zi? i?le ayriştirilmasien_US
dc.typeConference Objecten_US

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