Combined neural network model employing wavelet coefficients for EEG signals classification-Reference-Cited by-同舟云学术

Combined neural network model employing wavelet coefficients for EEG signals classification

Published:2009-03 Issue:2 Volume:19 Page:297-308
ISSN:1051-2004
Container-title:Digital Signal Processing
language:en
Short-container-title:Digital Signal Processing

Author:

Übeyli Elif Derya

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Signal Processing,Artificial Intelligence,Applied Mathematics,Computer Vision and Pattern Recognition,Statistics, Probability and Uncertainty,Computational Theory and Mathematics

Reference32 articles.

1. Classification of EEG signals using the wavelet transform;Hazarika;Signal Process.,1997

2. Analysis of EEG signals using Lyapunov exponents;Übeyli;Neural Network World,2006

3. Waveform detection with RBF network—Application to automated EEG analysis;Saastamoinen;Neurocomputing,1998

4. Analysis of EEG signals by combining eigenvector methods and multiclass support vector machines;Übeyli;Comput. Biol. Med.,2008

5. Fuzzy similarity index employing Lyapunov exponents for discrimination of EEG signals;Übeyli;Neural Network World,2006

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