Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7315
Title: Probabilistic neural networks employing Lyapunov exponents for analysis of Doppler ultrasound signals
Authors: Übeyli, Elif Derya
Keywords: Doppler ultrasound signals
chaotic signal
Lyapunov exponents
probabilistic neural network
Issue Date: 2008
Publisher: Pergamon-Elsevier Science Ltd
Abstract: The implementation of probabilistic neural networks (PNNs) with the Lyapunov exponents for Doppler ultrasound signals classification is presented. This study is directly based on the consideration that Doppler ultrasound signals are chaotic signals. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. Decision making was performed in two stages: computation of Lyapunov exponents as representative features of the Doppler ultrasound signals and classification using the PNNs trained on the extracted features. The present research demonstrated that the Lyapunov exponents are the features which well represent the Doppler ultrasound signals and the PNNs trained on these features achieved high classification accuracies. (C) 2007 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.compbiomed.2007.07.004
https://hdl.handle.net/20.500.11851/7315
ISSN: 0010-4825
1879-0534
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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