Chaotic Neural Network with Nonlinear Function Self-feedback

摘要：

　　Chaotic neural networks can acquire the ability to escape local minima of energy functions by chaotic dynamics.A Novel Chaotic neural network model with nonlinear function self-feedback is proposed by introducing nonlinear function into self-feedback of chaotic neural network.The analyses of the optimization mechanism of the networks suggest that nonlinear function self-feedback affects the original Hopfield energy function in the manner of the sum of the multiplications of nonlinear function to the state,avoiding the network being trapped into the local minima.We constructed the energy function of chaotic neural network,and analyzed the sufficient condition for the networks to reach asymptotical stability and set the parameter set of the networks for solving traveling salesman problem(TSP).Simulation results indicate that the novel chaotic neural networks can find the optimal solution of combinatorial optimization problems.

关键词： Chaotic neural network Nonlinear function self-feedback Energy function Asymptotical stability

作者: XU Yaoqun ZHAO Tingting

作者单位: Institute of System Engineering,Harbin University of Commerce,Harbin,150028

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 5075-5079

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）