Global robust exponential stability analysis for delayed recurrent neural networks

摘要：

This paper provides a new suf .cient condition for the global robust exponential stability of a delayed recurrent neural network.The conditions are expressed in terms of LMIs, which can be easily checked by various recently developed algorithms in solving convex optimization problems.Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition.

关键词： Delayed recurrent neural networks Global exponential stability Interval systems Linear matrix inequality

作者: Zhizhou Zhang Lingling Zhang Longhua She Lihong Huang

作者单位: Department of Mechatronics Engineering and Automation National University of Defense Technology Chan Department of Mathematics and Econometrics University of Hunan Changcha,Hunan Province,China

会议类型: 国际会议

会议名称: 2008 IEEE International Conference on Onformation and Automation(IEEE 信息与自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 499-503

在线出版日期: 2008-06-20（万方平台首次上网日期，不代表论文的发表时间）