Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7268
Full metadata record
DC FieldValueLanguage
dc.contributor.authorÜbeyli, Elif Derya-
dc.contributor.authorGüler, İnan-
dc.date.accessioned2021-09-11T15:56:11Z-
dc.date.available2021-09-11T15:56:11Z-
dc.date.issued2007en_US
dc.identifier.issn0045-7906-
dc.identifier.urihttps://doi.org/10.1016/j.compeleceng.2006.02.003-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7268-
dc.description.abstractIn this study, ophthalmic arterial Doppler signals recorded from 214 subjects were processed using classical, model-based, and eigenvector methods. The classical method (fast Fourier transform), two model-based methods (Burg autoregressive, least squares modified Yule-Walker autoregressive moving average methods), and three eigenvector methods (Pisarenko, multiple signal classification, and Minimum-Norm methods) were selected for performing spectral analysis of the ophthalmic arterial Doppler signals. Doppler power spectral density estimates of the ophthalmic arterial Doppler signals were obtained using these spectrum analysis techniques. The variations in the shape of the Doppler power spectra were examined in order to detect variabilities such as stenosis, ocular Behcet disease, and uveitis disease in the physical state of ophthalmic arterial Doppler signals. These power spectra were then used to compare the applied methods in terms of their frequency resolution and the effects in detecting stenosis, Behcet disease and uveitis disease in ophthalmic arteries. (c) 2006 Elsevier Ltd. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofComputers & Electrical Engineeringen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDoppler signalen_US
dc.subjectspectral analysisen_US
dc.subjectpower spectral densityen_US
dc.subjectophthalmic arterial disordersen_US
dc.titlePerformance analysis of classical, model-based and eigenvector methods: Ophthalmic arterial disorders detection caseen_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.volume33en_US
dc.identifier.issue1en_US
dc.identifier.startpage30en_US
dc.identifier.endpage47en_US
dc.identifier.wosWOS:000243819200003en_US
dc.identifier.scopus2-s2.0-33750721675en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.doi10.1016/j.compeleceng.2006.02.003-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ3-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

2
checked on Nov 16, 2024

WEB OF SCIENCETM
Citations

2
checked on Nov 2, 2024

Page view(s)

50
checked on Nov 11, 2024

Google ScholarTM

Check




Altmetric


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