Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5882
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dc.contributor.authorÜbeyli, Elif Derya-
dc.date.accessioned2021-09-11T15:20:33Z-
dc.date.available2021-09-11T15:20:33Z-
dc.date.issued2007en_US
dc.identifier.issn1300-1884-
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/71224-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5882-
dc.description.abstractIn this study, the automated diagnostic systems employing diverse and composite features for Doppler ultrasound signals, electroencephalogram (EEG) and electrocardiogram (ECG) signals were analyzed and their accuracies were determined. In pattern recognition applications, diverse features are extracted from raw data which needs recognizing. Combining multiple classifiers with diverse features are viewed as a general problem in various application areas of pattern recognition. The classification accuracies of multilayer perceptron neural network, combined neural network, and mixture of experts trained on composite feature and modified mixture of experts trained on diverse features were compared. The inputs of these automated diagnostic systems composed of diverse or composite features and were chosen according to the network structures. The conclusions of this study demonstrated that the modified mixture of experts trained on diverse features achieved accuracy rates which were higher than that of the other automated diagnostic systems trained on composite features.en_US
dc.language.isotren_US
dc.relation.ispartofJournal of the Faculty of Engineering and Architecture of Gazi Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAutomated diagnostic systemsen_US
dc.subjectBiomedical signalsen_US
dc.subjectComposite featuresen_US
dc.subjectDiverse featuresen_US
dc.titleBiyomedikal işaretlerin sınıflandırılmasında otomatik teşhis sistemlerinin başarımıen_US
dc.title.alternativePerformance of automated diagnostic systems in classification of biomedical 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.volume22en_US
dc.identifier.issue3en_US
dc.identifier.startpage461en_US
dc.identifier.endpage469en_US
dc.identifier.scopus2-s2.0-37849031557en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
dc.identifier.trdizinid71224en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1tr-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
TR Dizin İndeksli Yayınlar / TR Dizin Indexed Publications Collection
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