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

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Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal ClassificationFecha
2013Cita bibliográfica
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
Resumen
[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.
Palabras clave
Artificial neural networks
ANNs
Genetic algorithms
GAs
Signal classification
Epilepsy detection
ANNs
Genetic algorithms
GAs
Signal classification
Epilepsy detection
Versión del editor
ISSN
1759-1163
1759-1171
1759-1171