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A variable-parameter neural network trained by improved genetic algorithm and its application

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3 Author(s)
Ling, S.H. ; Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., China ; Lam, H.K. ; Leung, F.H.F.

This paper presents a neural network with variable parameters. These variable parameters adapt to the changes of the input environment, and tackle different input data sets in a large domain. Each input data set is effectively handled by its corresponding set of network parameters. Thus, the proposed neural network exhibits a better learning and generalization ability than a traditional one. An improved genetic algorithm (Lam et al., 2004) is proposed to train the network parameters. An application example on hand-written pattern recognition will be presented to verify and illustrate the improvement.

Published in:

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on  (Volume:3 )

Date of Conference:

31 July-4 Aug. 2005