Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7080
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dc.contributor.authorÜbeyli, Elif Derya-
dc.date.accessioned2021-09-11T15:45:24Z-
dc.date.available2021-09-11T15:45:24Z-
dc.date.issued2007en_US
dc.identifier.citation29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society -- AUG 22-26, 2007 -- Lyon, FRANCEen_US
dc.identifier.isbn978-1-4244-0787-3-
dc.identifier.issn1094-687X-
dc.identifier.urihttps://doi.org/10.1109/IEMBS.2007.4352598-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7080-
dc.description.abstractIn this paper, the usage of diverse features in detecting variability of electroencephalogram (EEG) signals was presented. The classification accuracies of modified mixture of experts (MATE), which were trained on diverse features, were obtained. The wavelet coefficients 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 diverse features achieved high accuracy rates.en_US
dc.description.sponsorshipIEEE Engn Med & Biol Socen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2007 Annual International Conference of The IEEE Engineering In Medicine And Biology Society, Vols 1-16en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectmodified mixture of expertsen_US
dc.subjectwavelet coefficientsen_US
dc.subjectLyapunov exponentsen_US
dc.subjectdiverse featuresen_US
dc.titleModified mixture of experts for analysis of EEG signalsen_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesPROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETYen_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.startpage1546en_US
dc.identifier.endpage1549en_US
dc.identifier.wosWOS:000253467001072en_US
dc.identifier.scopus2-s2.0-57649155303en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.pmid18002264en_US
dc.identifier.doi10.1109/IEMBS.2007.4352598-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference29th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Societyen_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
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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