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

Daniel Rivero, Vanessa Aguiar-Pulido, Enrique Fernandez-Blanco and Marcos Gestal

International Journal of Data Mining, Modelling and Management, 2013, vol. 5, issue 2, 182-191

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.

Keywords: artificial neural networks; ANNs; genetic algorithms; GAs; signal classification; epilepsy detection; EEG signals; signal classification; electroencephalogram; epileptic patients. (search for similar items in EconPapers)
Date: 2013
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