EXPONENTIAL STABILITY FOR STOCHASTIC NEURAL NETWORKS OF NEUTRAL TYPE WITH IMPULSIVE EFFECTS

被引：41
|
作者：
Sakthivel, Rathinasamy [1 ]
Samidurai, R. [2 ]
Anthoni, S. Marshal [3 ]
机构：
[1] Sungkyunkwan Univ, Dept Math, Suwon 440746, South Korea
[2] Periyar Univ, Dept Math, Salem 636011, India
[3] Anna Univ Coimbatore, Dept Math, Coimbatore 641047, Tamil Nadu, India
来源：
MODERN PHYSICS LETTERS B | 2010年 / 24卷 / 11期
关键词：
Stochastic neutral neural networks; impulsive effects; global exponential stability; linear matrix inequality; TIME-VARYING DELAYS; GLOBAL ASYMPTOTIC STABILITY; DISTRIBUTED DELAYS; ROBUST STABILITY; DISCRETE; CRITERIA;
D O I：
10.1142/S0217984910023141
中图分类号：
O59 [应用物理学];
学科分类号：
摘要：
This paper is concerned with the exponential stability of stochastic neural networks of neutral type with impulsive effects. By employing the Lyapunov functional and stochastic analysis, a new stability criterion for the stochastic neural network is derived in terms of linear matrix inequality. A numerical example is provided to show the effectiveness and applicability of the obtained result.
引用
收藏
页码：1099 / 1110
页数：12
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