Multistability and multiperiodicity of delayed bidirectional associative memory neural networks with discontinuous activation functions

被引：60
|
作者：
Huang, Yujiao [1 ]
Zhang, Huaguang [1 ]
Wang, Zhanshan [1 ]
机构：
[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2012年 / 219卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Multistability; Multiperiodicity; Bidirectional associative memory neural network; Discontinuous activation function; GLOBAL EXPONENTIAL STABILITY; TIME-VARYING DELAYS; REACTION-DIFFUSION TERMS; DISTRIBUTED DELAYS; CONVERGENCE; EXISTENCE; CRITERION;
D O I：
10.1016/j.amc.2012.06.068
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, the multistability and multiperiodicity issues are discussed for 2n-dimensional delayed bidirectional associative memory neural networks with r-level discontinuous activation functions. Sufficient conditions are established to ensure the existence of r(n) locally exponentially stable equilibria. As an extension of multistability, conditions are established to ensure the existence of r(n) locally exponentially stable periodic solutions when external inputs are periodic. Finally, two examples are given to illustrate the effectiveness of the obtained results. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码：899 / 910
页数：12
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