New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay  

作　　者：ZHANG HuaGuang WANG ZhanShan 

机构地区：[1]School of Information Science and Engineering [2] Northeastern University [3] Shenyang 110004 [4] China

出　　处：《Science in China(Series F)》2009年第6期942-948,共7页中国科学（F辑英文版）

基　　金：Supported by the National Natural Science Foundation of China (Grant Nos 60534010, 60728307, 60774048, 60774093);the Program for Cheung Kong Scholars and Innovative Research Groups of China (Grant No 60521003);the National High-Tech Research & Development Programof China (Grant No 2006AA04Z183);China Postdoctoral Sciencer Foundation (Grant No 20080431150); the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No 200801451096)

摘　　要：This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying delay.By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size of derivative of time varying delay.Two numerical examples show the effectiveness of the obtained results.This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying delay.By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size of derivative of time varying delay.Two numerical examples show the effectiveness of the obtained results.

关 键 词：recurrent neural networks global asymptotic stability linear matrix inequality （LMI） time-varying delay 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] Q141[自动化与计算机技术—控制科学与工程]