Delay dependent stability criteria for recurrent neural networks with time varying delays  

作　　者：Zhanshan WANG Huaguang ZHANG 

机构地区：[1]School of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110004, China

出　　处：《控制理论与应用（英文版）》2009年第1期9-13,共5页

基　　金：supported by the National Natural Science Foundation of China (No.60534010,60572070,60728307,60774048,60774093);the Program for Cheung Kong Scholars and Innovative Research Groups of China (No.60521003);the National High Technology Research and Development Program of China (No.2006AA04Z183);the Postdoctor Foundation of Northeastern University (No.20080314);the Natural Science Foundation of Liaoning Province (No.20072025);China Postdoctoral Science Foundation (20080431150)

摘　　要：This paper aims to present some delay-dependent global asymptotic stability criteria for recurrent neural networks with time varying delays. The obtained results have no restriction on the magnitude of derivative of time varying delay, and can be easily checked due to the form of linear matrix inequality. By comparison with some previous results, the obtained results are less conservative. A numerical example is utilized to demonstrate the effectiveness of the obtained results.This paper aims to present some delay-dependent global asymptotic stability criteria for recurrent neural networks with time varying delays. The obtained results have no restriction on the magnitude of derivative of time varying delay, and can be easily checked due to the form of linear matrix inequality. By comparison with some previous results, the obtained results are less conservative. A numerical example is utilized to demonstrate the effectiveness of the obtained results.

关 键 词：Recurrent neural networks STABILITY Time varying delay Linear matrix inequality 

分 类 号：O231[理学—运筹学与控制论] TP183[理学—数学]