Gauss-Morlet-Sigmoid Chaotic Neural Networks
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.
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