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Automatic detection of epileptic seizure using time-frequency distributions

Abstract:
The aim of this work is to introduce a new method based on time frequency distribution for classifying the EEG signals. Some parameters are extracted using time-frequency distribution as inputs to a feed-forward backpropagation neural networks (FBNN). The proposed method had better results with 98.25% accuracy compared to previously studied methods such as wavelet transform, entropy, logistic regression and Lyapunov exponent.

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Publisher copy:
10.1049/cp:20060378
Host title:
IET Conference Publications
Issue:
520
Pages:
29-29
Publication date:
2006-01-01
DOI:
ISBN-10:
0863416586
ISBN-13:
9780863416583
Keywords:
Pubs id:
pubs:287043
UUID:
uuid:d3d75cff-86ec-4bea-851b-c1b60416ed09
Local pid:
pubs:287043
Source identifiers:
287043
Deposit date:
2014-07-25

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