NDLI: Wavelet chaotic neural network with nonlinear self-feedback and its application to traveling salesman problem

Content Provider	IEEE Xplore Digital Library
Author	Ming Sun Lin Zhao Chao Yan Yao Qun Xu
Copyright Year	2008
Description	Author affiliation: Dept. of Autom., Harbin Eng. Univ., Harbin (Ming Sun; Lin Zhao; Chao Yan)
Abstract	Chaotic neural network has been proved to be a powerful tool to solve combinational optimization problems. Wavelet chaotic neural network is a kind of chaotic neural network with non-monotonous activation function composed by Sigmoid and Wavelet. In this paper, first a wavelet chaotic neural network model with different nonlinear self-feedbacks is proposed and the effects of the different self-feedbacks on simulated annealing are analyzed respectively. Then the proposed model is applied to the typical combinational optimization problem-10-city traveling salesman problem (TSP) and the numerical simulations show that the model can converge to the global optimal or near-optimal solutions more efficiently than the Hopfield network and that the model with Gauss wavelet self-feedback is superior to the model with other self-feedback in performance. Finally, the dynamics of the chaotic neural network model for the 10-city TSP is researched.
Starting Page	4553
Ending Page	4556
File Size	123898
Page Count	4
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4593656
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Simulated annealing Optimization Numerical models Mathematical model Neurons Chaos Wavelet chaotic neural network Nonlinear self-feedback
Content Type	Text
Resource Type	Article

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