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Title: AR ve ARMA metotlarının kullanımı ile teşhis sistemleri için öznitelik çıkarma: Oftalmik atardamar doppler işaretlerinin durum analizi
Other Titles: Feature extraction for diagnostic systems by usage of AR and ARMA methods: Ophthalmic arterial Doppler signals case study
Authors: Übeyli, Elif Derya
Güler, İnan
Keywords: AR method
ARMA method
Classification accuracy
Doppler power spectral density
Feature extraction
Ophthalmic artery
Issue Date: 2004
Abstract: For 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.
ISSN: 1300-1884
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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