Mean square global asymptotic stability of stochastic recurrent neural networks with distributed delays

被引：54
作者：
Guo, Yingxin [1 ]
机构：
[1] Qufu Normal Univ, Dept Math, Qufu 273165, Shandong, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2009年 / 215卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Stochastic neural networks with delays; Lyapunov functionals; Matrix inequality; Global asymptotic stability; EXPONENTIAL STABILITY; TIME-DELAYS; DISCRETE;
D O I：
10.1016/j.amc.2009.06.002
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
By constructing suitable Lyapunov functionals and combining with matrix inequality technique, a new simple sufficient condition is presented for the global asymptotic stability in the mean square of delayed neural networks. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码：791 / 795
页数：5
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