Recurrent neural networks employing Lyapunov exponents for EEG signals classification

@article{Gler2005RecurrentNN,
  title={Recurrent neural networks employing Lyapunov exponents for EEG signals classification},
  author={Nihal Fatma G{\"u}ler and Elif Derya {\"U}beyli and Inan G{\"u}ler},
  journal={Expert Syst. Appl.},
  year={2005},
  volume={29},
  pages={506-514}
}
There are a number of different quantitative models that can be used in a medical diagnostic decision support system including parametric methods, non-parametric methods and several neural network models. Unfortunately, there is no theory available to guide model selection. The aim of this study is to evaluate the diagnostic accuracy of the recurrent neural networks (RNNs) employing Lyapunov exponents trained with Levenberg–Marquardt algorithm on the electroencephalogram (EEG) signals. An… CONTINUE READING
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