Stability analysis of inertial Cohen-Grossberg-type neural networks with time delays

被引：87

作者：

Ke, Yunquan ^{[1
]}

Miao, Chunfang ^{[1
]}

机构：

[1] Shaoxing Univ, Dept Math, Shaoxing 312000, Zhejiang, Peoples R China

来源：

NEUROCOMPUTING | 2013年 / 117卷

关键词：

Inertial Cohen-Grossberg-type; Neural networks; Homeomorphism; Lyapunov functional; Differential mean value theorem; Exponential stability; REACTION-DIFFUSION; EXPONENTIAL STABILITY; DISTRIBUTED DELAYS; VARYING DELAYS; SYNCHRONIZATION; CHAOS; MODEL;

D O I：

10.1016/j.neucom.2013.01.026

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, the global exponential stability of inertial Cohen-Grossberg-type neural networks with time delays is investigated. First, by properly chosen variable substitution the system is transformed to the first order differential equation. Second, some sufficient conditions which can ensure the global exponential stability of the system are obtained using homeomorphism and differential mean value theorem, applying the analysis method and inequality technique. Finally, two examples are given to illustrate the effectiveness of the results. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：196 / 205

页数：10

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