Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6483
Title: Decision support systems for time-varying biomedical signals: EEG signals classification
Authors: Übeyli, Elif Derya
Keywords: Automated diagnostic systems
Spectral analysis techniques
Feature extraction/selection
EEG signals
Issue Date: 2009
Publisher: Pergamon-Elsevier Science Ltd
Abstract: An integrated view of the automated diagnostic systems combined with spectral analysis techniques in the classification of electroencephalogram (EEG) signals is presented. The paper includes illustrative and detailed information about implementation of automated diagnostic systems and feature extraction/selection from the EEG signals. The major objective of the paper is to be it guide for the readers, who want to develop an automated diagnostic system for classification of the EEG signals. Toward achieving this objective, this paper presents the techniques which should be considered in developing automated diagnostic systems. The author suggests that the content of the paper will assist to the people in gaining it better understanding of the techniques in the classification of the EEG signals. (C) 2007 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.eswa.2007.12.025
https://hdl.handle.net/20.500.11851/6483
ISSN: 0957-4174
1873-6793
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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