Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7268
Title: Performance analysis of classical, model-based and eigenvector methods: Ophthalmic arterial disorders detection case
Authors: Übeyli, Elif Derya
Güler, İnan
Keywords: Doppler signal
spectral analysis
power spectral density
ophthalmic arterial disorders
Issue Date: 2007
Publisher: Pergamon-Elsevier Science Ltd
Abstract: In 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.
URI: https://doi.org/10.1016/j.compeleceng.2006.02.003
https://hdl.handle.net/20.500.11851/7268
ISSN: 0045-7906
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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