Existence and global exponential stability of almost periodic solution for delayed competitive neural networks with discontinuous activations

被引：32
|
作者：
Tan, Yanxiang [1 ]
Jing, Ke [2 ]
机构：
[1] Univ Sci & Technol, Coll Math & Comp Sci, Changsha 410114, Hunan, Peoples R China
[2] Fuyang Normal Univ, Sch Math & Stat, Fuyang 236041, Anhui, Peoples R China
来源：
MATHEMATICAL METHODS IN THE APPLIED SCIENCES | 2016年 / 39卷 / 11期
基金：
中国国家自然科学基金;
关键词：
delay competitive neural networks; discontinuous activation; almost periodic solution; global exponential stability; DIFFERENT TIME SCALES; DYNAMICAL BEHAVIORS; DISSIPATIVITY; SYNCHRONIZATION; CONVERGENCE; INCLUSIONS;
D O I：
10.1002/mma.3732
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we study a class of delayed competitive neural networks with discontinuous activations. Without assuming the boundedness and local Lipschizian on the activation functions, some new criteria ensuring the existence and global exponential stability of almost periodic solutions for the neural network model considered in this work are established by constructing some suitable Lyapunov functionals and employing the theory of nonsmooth analysis. Finally, we present some applications and numerical examples with simulations to show the effectiveness of our main results. Copyright (C) 2016 JohnWiley & Sons, Ltd.
引用
收藏
页码：2821 / 2839
页数：19
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