Existence and global exponential stability of periodic solution for delayed neural networks with impulsive and stochastic effects

被引：50

作者：

Li, Xiaodi ^{[1
]}

机构：

[1] Xiamen Univ, Sch Math Sci, Xiamen 361005, Peoples R China

来源：

NEUROCOMPUTING | 2010年 / 73卷 / 4-6期

关键词：

Global exponential stability; Existence; Periodic solution; Delayed neural networks; L-operator; Impulses; Stochastic; TIME-VARYING DELAYS; CONTINUOUSLY DISTRIBUTED DELAYS; ROBUST STABILITY; ASYMPTOTIC STABILITY; DIFFERENTIAL-EQUATIONS; P-STABILITY; PERTURBATIONS;

D O I：

10.1016/j.neucom.2009.10.016

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, we investigate a class of delayed neural networks with impulsive and stochastic effects. By establishing an L-operator delay differential inequality with impulses and using the stochastic analysis technique, some Sufficient conditions are derived to ensure the existence and global exponential stability of periodic solution for the addressed neural networks. Those conditions only including related parameters of neural networks can be easily checked by simple algebraic methods. Finally, two examples and their simulations are given to show the feasibility and effectiveness of our results. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：749 / 758

页数：10

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