New Delay-dependent Global Asymptotic Stability Condition for Hopfield Neural Networks with Time-varying Delays  

作　　者：Guang-Deng Zong Jia Liu 

机构地区：[1]Research Institute of Automation, Qufu Normal University, Qufu 273165, PRC

出　　处：《International Journal of Automation and computing》2009年第4期415-419,共5页国际自动化与计算杂志（英文版）

基　　金：supported by National Natural Science Foundation of China (No. 60674027, 60875039, 60904022 and 60974127);Specialized Research Fund for the Doctoral Program of Higher Education (No. 20050446001);China Postdoctoral Science Foundation(No. 20070410336);Postdoctoral Foundation of Jiangsu Province(No. 0602042B);Scientific Research Foundation of Qufu Normal University

摘　　要：This paper deals with the global asymptotic stability problem for Hopfield neural networks with time-varying delays. By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in terms of linear matrix inequalities （LMIs）, which can be easily checked by utilizing the recently developed algorithms for solving LMIs. Examples are provided to demonstrate the effectiveness and reduced conservatism of the proposed condition.This paper deals with the global asymptotic stability problem for Hopfield neural networks with time-varying delays. By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in terms of linear matrix inequalities （LMIs）, which can be easily checked by utilizing the recently developed algorithms for solving LMIs. Examples are provided to demonstrate the effectiveness and reduced conservatism of the proposed condition.

关 键 词：Global asymptotic stability Hopfield neural networks linear matrix inequality （LMI） time-varying delays Lyapunov-Krasovskii functional. 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] O175.26[自动化与计算机技术—控制科学与工程]