A new result on global exponential robust stability of neural networks with time-varying delays  

作　　者：Jinliang SHAO Tingzhu HUANG 

机构地区：[1]School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu Sichuan 610054, China

出　　处：《控制理论与应用（英文版）》2009年第3期315-320,共6页

基　　金：supported by 973 Programs (No.2008CB317110);the Key Project of Chinese Ministry of Education (No.107098);Sichuan Province Project for Applied Basic Research (No.2008JY0052);the Project for Academic Leader and Group of UESTC

摘　　要：In this paper, the global exponential robust stability of neural networks with ume-varying delays is investigated. By using nonnegative matrix theory and the Halanay inequality, a new sufficient condition for global exponential robust stability is presented. It is shown that the obtained result is different from or improves some existing ones reported in the literatures. Finally, some numerical examples and a simulation are given to show the effectiveness of the obtained result.In this paper, the global exponential robust stability of neural networks with ume-varying delays is investigated. By using nonnegative matrix theory and the Halanay inequality, a new sufficient condition for global exponential robust stability is presented. It is shown that the obtained result is different from or improves some existing ones reported in the literatures. Finally, some numerical examples and a simulation are given to show the effectiveness of the obtained result.

关 键 词：Neural networks Time-varying delays Global exponential robust stability 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TP18[自动化与计算机技术—控制科学与工程]