期刊
NEUROCOMPUTING
卷 70, 期 16-18, 页码 2799-2808出版社
ELSEVIER
DOI: 10.1016/j.neucom.2006.06.010
关键词
Artificial Neural Networks; Connectionist Systems; Genetic Algorithms; brain computational models; hybrid learning method
Recent studies have confirmed that the modulation of synaptic efficacy affects emergent behaviour of brain cells assemblies. We report the first results of adding up the behaviour of particular brain circuits to Artificial Neural Networks. A new hybrid learning method has emerged. In order to find the best solution to a given problem, this method combines the use of Genetic Algorithms with particular changes to connection weights based on this behaviour. We show this combination in feed-forward multilayer architectures initially created to solve classification problems and we illustrate the benefits obtained with this new method. (c) 2007 Elsevier B.V. All rights reserved.
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