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Using genetic algorithms for automatic recurrent ANN development: an application to EEG signal classification

Author

Listed:
  • Daniel Rivero
  • Vanessa Aguiar-Pulido
  • Enrique Fernandez-Blanco
  • Marcos Gestal

Abstract

ANNs are one of the most successful learning systems. For this reason, many techniques have been published that allow the obtaining of feed-forward networks. However, few works describe techniques for developing recurrent networks. This work uses a genetic algorithm for automatic recurrent ANN development. This system has been applied to solve a well-known problem: classification of EEG signals from epileptic patients. Results show the high performance of this system, and its ability to develop simple networks, with a low number of neurons and connections.

Suggested Citation

  • Daniel Rivero & Vanessa Aguiar-Pulido & Enrique Fernandez-Blanco & Marcos Gestal, 2013. "Using genetic algorithms for automatic recurrent ANN development: an application to EEG signal classification," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 5(2), pages 182-191.
    • Handle: RePEc:ids:ijdmmm:v:5:y:2013:i:2:p:182-191
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