Improved delay-partitioning method to stability analysis for neural networks with discrete and distributed time-varying delays

被引：72
|
作者：
Tian, Junkang [1 ]
Xiong, Wenjun [1 ]
Xu, Fang [1 ]
机构：
[1] Southwest Petr Univ, Sch Sci, Chengdu 610500, Sichuan, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2014年 / 233卷
基金：
中国国家自然科学基金;
关键词：
Neural networks; Stability analysis; Time-varying delay; Delay-partitioning method; DEPENDENT EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; ROBUST STABILITY; STATE ESTIMATION; CRITERIA; DYNAMICS;
D O I：
10.1016/j.amc.2014.01.129
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, an improved method is derived for the delay-dependent stability problem of neural networks with discrete and distributed time-varying delays. An improved Lyapunov functional is constructed by introducing the newly delay-partitioning method and considering the sufficient information of neuron activation functions. By using the relationship between each subinterval and time-varying delay sufficiently, a new delay-dependent stability criterion has been obtained to reduce the conservatism. Two numerical examples are finally given to show the merits of the derived conditions. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码：152 / 164
页数：13
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