Gauss-Morlet-Sigmoid chaotic neural networks

Authors:
Yao-qun Xu;Ming Sun
Affiliations:
Institute of System Engineering, Harbin University of Commerce, Harbin, China;Institute of System Engineering, Harbin University of Commerce, Harbin, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

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Abstract

Chaotic neural networks have been proved to be powerful tools for escaping from local minima. In this paper, we first retrospect Chen’s chaotic neural network and then propose a novel Gauss-Morlet-Sigmoid chaotic neural network model. Second, we make an analysis of the largest Lyapunov exponents of the neural units of Chen’s and the Gauss-Morlet-Sigmoid model. Third, 10-city traveling salesman problem (TSP) is given to make a comparison between them. Finally we conclude that the novel chaotic neural network model is more effective.