Using genetic algorithms for automatic recurrent ANN development: an application to EEG signal classification
by Daniel Rivero; Vanessa Aguiar-Pulido; Enrique Fernandez-Blanco; Marcos Gestal
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 5, No. 2, 2013

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.

Online publication date: Tue, 29-Jul-2014

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