Abstract
A new chaotic neural network model called Morlet Wavelet chaotic neural network with chaotic noise was presented, the chaotic noise was produced by the Logistic map multiplied by an exponentially decreased variable factor in order to verify the ability of anti-disturbance, and the transiently chaotic mechanism was introduced by the attenuation of the self-feedback connection weight. In this paper, first, the figures of the reversed bifurcation and the maximal Lyapunov exponents of single neural unit were given. Second, the new model was applied to solve function optimizations. Finally, 10-city traveling salesman problem was given and simultaneously the effects of the proportional value of the non-monotonous-function coefficient to the monotonous-function coefficient in the model were discussed. As seen from the simulation results, the new model is more powerful than common chaotic neural network and has some certain ability of anti-disturbance.
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Xu, Yq., Zhang, Jh., Sun, M. (2007). Morlet Wavelet Chaotic Neural Network with Chaotic Noise. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_143
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DOI: https://doi.org/10.1007/978-3-540-74282-1_143
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74281-4
Online ISBN: 978-3-540-74282-1
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