A New Model of Chaotic Neural Network Simulated Annealin and its Application

摘要：

Unlike the gradient descent neural network, the chaotic neural networks have more complex dynamics. A kind of chaotic neural network is presented，which combines stochastic with deterministic property to introduce chaos mechanism into Hopfield neural network to coarsely search the optimum under chaotic dynamics and control the chaotic dynamics by annealing strategy to perform inverse bifurcation and disappear. After that, the gradient property of HNN is used to reach stable point. Simulation results show that such an algorithm can avoid getting stuck in local minima.

关键词： chaotic neural networks simulated annealin

作者: Jiahai Zhang Chuanfeng Sun Yaoqun Xu

作者单位: Department of Electrical Engineering, Sanjiang University, Nanjing 210012,China Department of Electrical Engineering, Sanjiang University, Nanjing 210012 Institute of System Engineering, Harbin University of Commerce, Harbin 150028, China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）