Robust Exponential Stability of Impulsive Stochastic Neural Networks with Leakage Time-Varying Delay

被引：0

作者：

Lu, Chunge ^{[1
]}

Wang, Linshan ^{[1
]}

机构：

[1] Ocean Univ China, Coll Math Sci, Qingdao 266100, Peoples R China

来源：

ABSTRACT AND APPLIED ANALYSIS | 2014年

基金：

美国国家科学基金会;

关键词：

SYSTEMS; PERTURBATIONS; TERM; BAM;

D O I：

10.1155/2014/831027

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper investigates mean-square robust exponential stability of the equilibrium point of stochastic neural networks with leakage time-varying delays and impulsive perturbations. By using Lyapunov functions and Razumikhin techniques, some easy-to-test criteria of the stability are derived. Two examples are provided to illustrate the efficiency of the results.

引用

页数：8

共 23 条

[21] Global exponential stability of static neural networks with delay and impulses: Discrete-time case [J].

Wu, Shu-Lin ;

Li, Ke-Lin ;

Huang, Ting-Zhu .

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2012, 17 (10) :3947-3960

[22] Robust exponential stability of uncertain impulsive neural networks with time-varying delays and delayed impulses [J].

Zhang, Yu .

NEUROCOMPUTING, 2011, 74 (17) :3268-3276

[23] Global exponential stability and periodicity of cellular neural networks with variable delays [J].

Zhao, HY .

PHYSICS LETTERS A, 2005, 336 (4-5) :331-341

← 1 2 3 →