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Shannon小波混沌神经网络及其TSP(城市旅行商)问题的求解
引用本文:徐耀群,孙 明.Shannon小波混沌神经网络及其TSP(城市旅行商)问题的求解[J].控制理论与应用,2008,25(3):574-577.
作者姓名:徐耀群  孙 明
作者单位:哈尔滨商业大学系统工程研究所,黑龙江,哈尔滨,150028
基金项目:黑龙江省自然科学基金,黑龙江省哈尔滨市青年科学基金,黑龙江省普通高等学校新世纪优秀人才培养计划
摘    要:混沌神经网络已经被证明是解决组合优化问题的有效工具.针对混沌神经网络的单调的激励函数,通过引入Shannon小波和Sigmoid函数加和组成的非单调激励函数,提出了一种新型的暂态混沌神经元模型.给出了该混沌神经元的倒分岔图和最大Lyapunov指数时间演化图,分析了其动力学特性.基于该模型,构造了一种暂态混沌神经网络,并将其应用于函数优化和组合优化问题.通过经典的10城市TSP验证了该暂态混沌神经网络的有效性.

关 键 词:非单凋激励函数  混沌神经网络  Lyapunov指数  Shannon小波  旅行商问题
收稿时间:2006/6/13 0:00:00
修稿时间:3/7/2007 12:00:00 AM

Shannon wavelet chaotic neural network and its solution to TSP (traveling salesman problem)
XU Yao-qun and SUN Ming.Shannon wavelet chaotic neural network and its solution to TSP (traveling salesman problem)[J].Control Theory & Applications,2008,25(3):574-577.
Authors:XU Yao-qun and SUN Ming
Affiliation:Institute of System Engineering, Harbin University of Commerce, Harbin Heilongjiang 150028, China;Institute of System Engineering, Harbin University of Commerce, Harbin Heilongjiang 150028, China
Abstract:Chaotic neural network has been proved to be a valid tool for solving combinational optimization problems. Referring to the monotonous activation function of chaotic neural network,we present a novel transient chaotic-neuron model by introducing the Shannon wavelet and the Sigmoid activation function to compose the non-monotonous activation function.The reversed bifurcation and the maximum Lyapunov exponent of the chaotic neuron are given and the dynamic system is analyzed.Based on the neuron model,a novel transient chaotic-neural network is made and applied to function- optimization and combinational optimization problems.The simulation results of TSP in 10 cities indicate the validity of this novel transient chaotic-neural network.
Keywords:non-monotonous activation function  chaotic neural network  Lyapunov exponent  Shannon wavelet  TSP
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