A genetic procedure used to train RFB neural networks

Authors:
Constantin-Iulian Vizitiu
Affiliations:
Communications and Electronic Systems Department, Military Technical Academy, Bucharest, Romania
Venue:
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
Year:
2010

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Abstract

The performance level assigned to RBF neural networks used inside of pattern recognition systems depends a lot by their training algorithms and especially, by the specific techniques (e.g., clustering techniques) used for RBF center positioning. Starting from basic property of genetic algorithms to represent global searching methods, a full-genetic procedure to assure optimization both connectivity and neural weights of RBF networks is described. To confirm the broached theoretical aspects and having as starting point a real pattern recognition task, a comparative study (as performance level) with others standard RBF training methods and SART neural network is also presented.