Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6136
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dc.contributor.authorGüler, İnan-
dc.contributor.authorÜbeyli, Elif Derya-
dc.date.accessioned2021-09-11T15:35:03Z-
dc.date.available2021-09-11T15:35:03Z-
dc.date.issued2006en_US
dc.identifier.issn0167-8655-
dc.identifier.issn1872-7344-
dc.identifier.urihttps://doi.org/10.1016/j.patrec.2006.03.001-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6136-
dc.description.abstractThe aim of this study is to evaluate the diagnostic accuracy of the recurrent neural networks (RNNs) trained with Levenberg-Marquardt algorithm on the Doppler ultrasound blood flow signals. The ophthalmic arterial (OA) and internal carotid arterial (ICA) Doppler signals were decomposed into time-frequency representations using discrete wavelet transform and statistical features were calculated to depict their distribution. The RNNs were implemented for diagnosis of OA and ICA diseases using the statistical features as inputs. We explored the ability of designed and trained Elman RNNs, combined with wavelet preprocessing, to discriminate the Doppler signals recorded from different healthy subjects and subjects suffering from OA and ICA diseases. The classification results demonstrated that the proposed combined wavelet/RNN approach can be useful in analyzing long-term Doppler signals for early recognition of arterial diseases. (c) 2006 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofPattern Recognition Lettersen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectrecurrent neural networksen_US
dc.subjectLevenberg-Marquardt algorithmen_US
dc.subjectsignal classificationen_US
dc.subjectautomatic diagnosisen_US
dc.subjectdiscrete wavelet transformen_US
dc.subjectdoppler signalen_US
dc.subjectophthalmic arteryen_US
dc.subjectinternal carotid arteryen_US
dc.titleA recurrent neural network classifier for Doppler ultrasound blood flow 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.volume27en_US
dc.identifier.issue13en_US
dc.identifier.startpage1560en_US
dc.identifier.endpage1571en_US
dc.identifier.wosWOS:000239355100016en_US
dc.identifier.scopus2-s2.0-33745839826en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.doi10.1016/j.patrec.2006.03.001-
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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