Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification
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http://hdl.handle.net/2183/20701Collections
- Investigación (FIC) [1591]
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Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal ClassificationDate
2013Citation
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
ANNs
Genetic algorithms
GAs
Signal classification
Epilepsy detection
Editor version
ISSN
1759-1163
1759-1171
1759-1171