Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform

The aim of this study is to detect epileptic seizure in EEG signals using a hybrid system based on decision tree classifier and fast Fourier transform (FFT). The present study proposes a hybrid system with two stages: feature extraction using FFT and decision making using decision tree classifier. T...

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Veröffentlicht in:	Applied mathematics and computation Jg. 187; H. 2; S. 1017 - 1026
Hauptverfasser:	Polat, Kemal, Güneş, Salih
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY Elsevier Inc 15.04.2007 Elsevier
Schlagworte:	Calculus of variations and optimal control Combinatorics Combinatorics. Ordered structures Decision tree classifier Designs and configurations Electroencephalogram (EEG) Epileptic seizure Exact sciences and technology FFT k-Fold cross-validation Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Sciences and techniques of general use Decision tree classifier k-Fold cross-validation Electroencephalogram (EEG) FFT Epileptic seizure Disease Fast Fourier transformation Cross validation Classifier Decision tree Depth Hybrid system Design Electrodes Accuracy Classification Evolution Diagnosis Intelligent system Decision making Cross classification Sensitivity Numerical analysis Applied mathematics Experimental design Feature extraction Detection Hippocampus
ISSN:	0096-3003, 1873-5649
Online-Zugang:	Volltext
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