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Shannon Wavelet Chaotic Neural Networks

  • Yao-qun Xu
  • Ming Sun
  • Ji-hong Shen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)

Abstract

Chaotic neural networks have been proved to be strong tools to solve the optimization problems. In order to escape the local minima, a new chaotic neural network model called Shannon wavelet chaotic neural network was presented. The activation function of the new model is non-monotonous, which is composed of sigmoid and Shannon wavelet. First, the figures of the reversed bifurcation and the maximal Lyapunov exponents of single neural unit were given. Second, the new model is applied to solve several function optimizations. Finally, 10-city traveling salesman problem is given and the effects of the non-monotonous degree in the model on solving 10-city traveling salesman problem are discussed. The new model can solve the optimization problems more effectively because of the Shannon wavelet being a kind of basic function. Seen from the simulation results, the new model is powerful.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yao-qun Xu
    • 1
    • 2
  • Ming Sun
    • 1
  • Ji-hong Shen
    • 2
  1. 1.Institute of System EngineeringHarbin University of CommerceHarbinChina
  2. 2.Department of MathematicsHarbin Engineering UniversityHarbinChina

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