Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5737
Full metadata record
DC FieldValueLanguage
dc.contributor.authorÜbeyli, Elif Derya-
dc.contributor.authorGüler, İnan-
dc.date.accessioned2021-09-11T15:19:49Z-
dc.date.available2021-09-11T15:19:49Z-
dc.date.issued2004en_US
dc.identifier.issn1300-1884-
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/38826-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5737-
dc.description.abstractFor diagnostic systems, features are extracted from signals by the usage of autoregressive (AR) and autoregressive moving average (ARMA) methods and power level-frequency distributions of the signals are demonstrated by statistical features. In the present study, spectral analysis of ophthalmic arterial Doppler signals obtained from different subjects was performed using the AR and ARMA methods and Doppler power spectral density values which contain a significant amount of information about the signal were considered as feature vectors representing the signal. In order to reduce the dimensionality of the extracted feature vectors, statistical processes were performed over the Doppler power spectral density values and input feature vectors of multilayer perceptron neural networks used in classification were selected. Performances of the AR and ARMA methods in the analysis of Doppler signals were determined by examining performances of multilayer perceptron neural networks trained by different algorithms. Total classification accuracies of the constructed networks were demonstrated that multilayer perceptron neural network trained by Levenberg-Marquardt algorithm which used ARMA Doppler power spectral density values as inputs could be used in classification of ophthalmic arterial Doppler signals.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/closedAccessen_US
dc.subjectAR methoden_US
dc.subjectARMA methoden_US
dc.subjectClassification accuracyen_US
dc.subjectDoppler power spectral densityen_US
dc.subjectFeature extractionen_US
dc.subjectOphthalmic arteryen_US
dc.titleAr ve Arma Metotlarının Kullanımı ile Teşhis Sistemleri için Öznitelik Çıkarma: Oftalmik Atardamar Doppler İşaretlerinin Durum Analizien_US
dc.title.alternativeFeature Extraction for Diagnostic Systems by Usage of Ar and Arma Methods: Ophthalmic Arterial Doppler Signals Case Studyen_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.volume19en_US
dc.identifier.issue4en_US
dc.identifier.startpage405en_US
dc.identifier.endpage413en_US
dc.identifier.scopus2-s2.0-11444264294en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
dc.identifier.trdizinid38826en_US
item.openairetypeArticle-
item.languageiso639-1tr-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
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
Show simple item record



CORE Recommender

Page view(s)

82
checked on Dec 23, 2024

Google ScholarTM

Check





Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.