Exponential stability of stochastic high-order BAM neural networks with time delays and impulsive effects

被引：8
|
作者：
Lu, Danjie [1 ]
Li, Chaojie [2 ]
机构：
[1] Chongqing Univ, Coll Resource & Environm Sci, Chongqing 630044, Peoples R China
[2] Univ Ballarat, Sch Sci Informat Technol & Engn, Ballarat, Vic 3353, Australia
来源：
NEURAL COMPUTING & APPLICATIONS | 2013年 / 23卷 / 01期
关键词：
Stochastic high-order BAM neural networks; Exponential stability; Time-varying delays; Impulsive effects; BIDIRECTIONAL ASSOCIATIVE MEMORIES; VARYING DELAYS; FUNCTION APPROXIMATION;
D O I：
10.1007/s00521-012-0861-1
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 consider the problem on exponential stability analysis of the stochastic impulsive high-order BAM neural networks with time delays. Through employing Lyapunov function method and stochastic bidirected halanay inequality, we constitute exponential stability of the stochastic impulsive high-order BAM neural networks with its estimated exponential convergence rate and feasible interval of impulsive strength. An example illustrates the main results.
引用
收藏
页码：1 / 8
页数：8
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