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

页码：1 / 8

页数：8

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