A Novel Chaotic Neural Network with Anti-trigonometric Function Self-feedback

摘要：

A Chaotic neural network model with anti-trigonometric function self-feedback is proposed by introducing anti-trigonometric function into self-feedback of chaotic neural network The analyses of the optimization mechanism of the networks suggest that anti-trigonometric function self-feedback affects the original Hopfield energy function in the manner of the sum of the multiplications of anti-trigonometric function to the state, avoiding the network being trapped into the local minima. The energy function is constructed, and the sufficient condition for the networks to reach asymptotical stability is analyzed and is used to instruct the parameter set of the networks for solving traveling salesman problem (TSP). Simulation research on function optimization and TSP indicates that the proposed networks can find the optimal solution of combinatorial optimization problems.

关键词： Anti-trigonometric function self-feedback Chaotic neural network Energy function Asymptotical

作者: Yaoqun Xu Xueling Yang

作者单位: Institute of System Engineering, Harbin University of Commerce, Harbin, 150028 Department of Mathematic, Harbin Engineering University, ,Harbin, 150001, China

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 3098-3103

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）