Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7079
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dc.contributor.authorÜbeyli, Elif Derya-
dc.date.accessioned2021-09-11T15:45:23Z-
dc.date.available2021-09-11T15:45:23Z-
dc.date.issued2009en_US
dc.identifier.issn0266-4720-
dc.identifier.issn1468-0394-
dc.identifier.urihttps://doi.org/10.1111/j.1468-0394.2009.00490.x-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7079-
dc.description.abstractThe use of diverse features in detecting variability of electroencephalogram (EEG) signals is presented. The classification accuracies of the modified mixture of experts (MME), which was trained on diverse features, were obtained. Eigenvector methods (Pisarenko, multiple signal classification - MUSIC, and minimum-norm) were selected to generate the power spectral density estimates. The features from the power spectral density estimates and Lyapunov exponents of the EEG signals were computed and statistical features were calculated to depict their distribution. The statistical features, which were used for obtaining the diverse features of the EEG signals, were then input into the implemented neural network models for training and testing purposes. The present study demonstrated that the MME trained on the diverse features achieved high accuracy rates (total classification accuracy of the MME is 98.33%).en_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofExpert Systemsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectmodified mixture of expertsen_US
dc.subjecteigenvector methodsen_US
dc.subjectLyapunov exponentsen_US
dc.subjectdiverse featuresen_US
dc.subjectelectroencephalogram (EEG) signalsen_US
dc.titleModified mixture of experts employing eigenvector methods and Lyapunov exponents for analysis of electroencephalogram signalsen_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.volume26en_US
dc.identifier.issue4en_US
dc.identifier.startpage339en_US
dc.identifier.endpage354en_US
dc.identifier.wosWOS:000269539900004en_US
dc.identifier.scopus2-s2.0-67649626328en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.doi10.1111/j.1468-0394.2009.00490.x-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
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
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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