STABILITY ANALYSIS OF HIGH-ORDER HOPFIELD-TYPE NEURAL NETWORKS BASED ON A NEW IMPULSIVE DIFFERENTIAL INEQUALITY

被引：9
|
作者：
Liu, Yang [1 ]
Yang, Rongjiang [1 ]
Lu, Jianquan [2 ]
Wu, Bo [1 ,3 ]
Cai, Xiushan [1 ]
机构：
[1] Zhejiang Normal Univ, Coll Math Phys & Informat Engn, Jinhua 321004, Peoples R China
[2] Southeast Univ, Dept Math, Nanjing 210096, Jiangsu, Peoples R China
[3] Zhejiang Normal Univ, Acad Affairs Div, Jinhua 321004, Peoples R China
来源：
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE | 2013年 / 23卷 / 01期
关键词：
impulsive differential inequality; globally exponential stability; high-order Hopfield-type neural network; GLOBAL EXPONENTIAL STABILITY; TIME-DELAY; CRITERIA; SYSTEMS; STABILIZATION;
D O I：
10.2478/amcs-2013-0016
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper is devoted to studying the globally exponential stability of impulsive high-order Hopfield-type neural networks with time-varying delays. In the process of impulsive effect, nonlinear and delayed factors are simultaneously considered. A new impulsive differential inequality is derived based on the Lyapunov-Razumikhin method and some novel stability criteria are then given. These conditions, ensuring the global exponential stability, are simpler and less conservative than some of the previous results. Finally, two numerical examples are given to illustrate the advantages of the obtained results.
引用
收藏
页码：201 / 211
页数：11
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