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Gauss-Morlet-Sigmoid Chaotic Neural Networks

  • Yao-qun Xu
  • Ming Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yao-qun Xu
    • 1
  • Ming Sun
    • 1
  1. 1.Institute of System EngineeringHarbin University of CommerceHarbinChina

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