Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6260
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dc.contributor.authorÜbeyli, Elif Derya-
dc.date.accessioned2021-09-11T15:35:31Z-
dc.date.available2021-09-11T15:35:31Z-
dc.date.issued2008en_US
dc.identifier.issn0010-4825-
dc.identifier.issn1879-0534-
dc.identifier.urihttps://doi.org/10.1016/j.compbiomed.2007.06.002-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6260-
dc.description.abstractA new approach based on the implementation of multiclass support vector machine (SVM) with the error correcting output codes (ECOC) is presented for classification of electroencephalogram (EEG) signals. In practical applications of pattern recognition, there are often diverse features extracted from raw data which needs recognizing. Decision making was performed in two stages: feature extraction by eigenvector methods and classification using the classifiers trained on the extracted features. The aim of the study is classification of the EEG signals by the combination of eigenvector methods and multiclass SVM. The purpose is to determine an optimum classification scheme for this problem and also to infer clues about the extracted features. The present research demonstrated that the eigenvector methods are the features which well represent the EEG signals and the multiclass SVM trained on these features achieved high classification accuracies. (C) 2007 Elsevier Ltd. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofComputers In Biology And Medicineen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectmulticlass support vector machine (SVM)en_US
dc.subjecteigenvector methodsen_US
dc.subjectelectroencephalogram (EEG) signalsen_US
dc.titleAnalysis of EEG signals by combining eigenvector methods and multiclass support vector machinesen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume38en_US
dc.identifier.issue1en_US
dc.identifier.startpage14en_US
dc.identifier.endpage22en_US
dc.identifier.wosWOS:000252918000002en_US
dc.identifier.scopus2-s2.0-37049007663en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.pmid17651716en_US
dc.identifier.doi10.1016/j.compbiomed.2007.06.002-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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