Asymptotic stability of BAM neural networks of neutral-type with impulsive effects and time delay in the leakage term

被引：40
|
作者：
Balasubramaniam, P. [1 ]
Vembarasan, V. [1 ]
机构：
[1] Gandhigram Rural Univ, Dept Math, Dindigul 624302, Tamilnadu, India
来源：
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2011年 / 88卷 / 15期
关键词：
BAM neural networks; impulses; linear matrix inequality; leakage term; neutral delay; GLOBAL EXPONENTIAL STABILITY; DISTRIBUTED DELAYS; DEPENDENT STABILITY; VARYING DELAYS; CRITERION;
D O I：
10.1080/00207160.2011.591388
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper presents asymptotic stability of bi-directional associative memory neural networks of the neutral-type with impulsive effects and time delay in the leakage term. Based on the topological degree theory, the Lyapunov method and the linear matrix inequality approach, some sufficient conditions are derived to ensure the existence, uniqueness and global asymptotic stability of the equilibrium point for the considered model. Finally, six numerical examples are given to illustrate the effectiveness and less conservatism of the derived results.
引用
收藏
页码：3271 / 3291
页数：21
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