| 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.[点击复制] |
| XU Yao-qun,SUN Ming.Shannon wavelet chaotic neural network and its solution to TSP (traveling salesman problem)[J].Control Theory and Technology,2008,25(3):574~577.[点击复制] |
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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 |
| Shannon wavelet chaotic neural network and its solution to TSP (traveling salesman problem) |
| 摘要点击 1929 全文点击 1600 投稿时间：2006-06-13 修订日期：2007-03-07 |
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| DOI编号 |
| 2008,25(3):574-577 |
| 中文关键词 非单调激励函数 混沌神经网络 Lyapunov指数 Shannon小波 旅行商问题 |
| 英文关键词 non-monotonous activation function chaotic neural network Lyapunov exponent Shannon wavelet TSP |
| 基金项目 黑龙江省自然科学基金资助项目(F200610); 哈尔滨市青年科学基金资助项目(2005AFQXJ040); 黑龙江省普通高等学校新世纪优秀人才培养计划资助项目(1153-NCET-008). |
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| 中文摘要 |
| 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. |
| 英文摘要 |
| 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 functionoptimization and combinational optimization problems. The simulation results of TSP in 10 cities indicate the validity of this novel transient chaotic-neural network. |