Exponential stability for switched neural networks with time-varying delays

摘要：

　　This paper is concerned with the problem of exponential stability for a class of switched neural networks with time-varying delays.Based on the average dwell time(ADT)technique,mode-dependent average dwell time(MDADT)technique and multiple Lyapunov-Krasovskii(LK)function approach,two conditions are derived to design switching signal and guarantee the exponential stability of the considered neural networks,which are delay-dependent and formulated by linear matrix inequalities(LMIs).Finally,Numerical examples confirm the effectiveness and less conservativeness of the proposed methods.

关键词： Exponential stability neural networks switched systems time-varying delay ADT MDADT

作者: Zheng-Fan Liu Chen-Xiao Cai Yun Zou

作者单位: The School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China

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: 4970-4976

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）