Classification of Epileptic EEG Signals using Time-Delay Neural Networks and Probabilistic Neural Networks

@article{Goshvarpour2013ClassificationOE,
  title={Classification of Epileptic EEG Signals using Time-Delay Neural Networks and Probabilistic Neural Networks},
  author={Ateke Goshvarpour and Hossein Ebrahimnezhad and Atefeh Goshvarpour},
  journal={International Journal of Information Engineering and Electronic Business},
  year={2013},
  volume={5},
  pages={59-67}
}
The aim of this paper is to investigate the performance of time delay neural networks (TDNNs) and the probabilistic neural networks (PNNs) trained with nonlinear features (Lyapunov exponents and Entropy) on electroencephalogram signals (EEG) in a specific pathological state. For this purpose, two types of EEG signals (normal and partial epilepsy) are analyzed. To evaluate the performance of the classifiers, mean square error (MSE) and elapsed time of each classifier are examined. The results… 

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