A New Model of Chaotic Neural Network Simulate Annealing and Its Application

摘要：

Knowledge on chaos is one of important achievements in nonlinear science. 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： Chaos Neural Networks Annealing

作者: Jiahai Zhang Shufan Shun Chuanfeng Shun

作者单位: College of Electrical and Automatic Engineering, Sanjing University, Nanjing 210012

会议类型: 国际会议

会议名称: 第四届亚太地区混沌控制与同步会议(The Fourth Asia-Pacific Workshop on Chaos Control and Synchronization)

会议地点: 哈尔滨

会议语种:英文

页码: 251-253

在线出版日期: 2007-08-24（万方平台首次上网日期，不代表论文的发表时间）