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Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification

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Title
Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification
Author(s)
Rivero, Daniel
Aguiar-Pulido, Vanessa
Fernández-Blanco, Enrique
Gestal, M.
Date
2013
Citation
Rivero D, Aguiar-Pulido V, Fernández-Blanco E, Gestal M. Using genetic algorithms for automatic recurrent ANN development: an application to EEG signal classification. Int J Data Mining Modelling Management. 2013;5(2):182-191
Abstract
[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, fe w works describe techniques for developing recurrent networks. This work uses a genetic algorithm for automatic recurrent ANN devel opment. This system has been applied to solve a well-known problem: classi fication 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
 
Editor version
https://doi.org/10.1504/IJDMMM.2013.053695
ISSN
1759-1163
1759-1171
 

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