Optimal Identification Method of Nonlinear System Based on GA-GHNNs P

摘要：

Gaussian-Hopfield neural network algorithm (GHNNs) is the most commonly used method of solving the identification problem of nonlinear systems, but learning rule (LMS rule) is easy to fall into local optimum. Genetic algorithm (GA) has globally optimal ability and can solve the locally optimal problem well. This paper puts forward GAGHNNs algorithm and uses GA algorithm to solve the optimum parameters of GHNNs network. And finally, it carries out simulation experiments to prove the validity of the algorithm. Simulation results also show that this method has the ability to distinguish nonlinear systems.

作者: Lin Xiao-fei Weng Mu-yun

作者单位: Telecommunication Engineering Institute Air Force University of Engineering Xi’an, 710077, China

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 2555-2557

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）