Global Exponential Stability of Antiperiodic Solution for Impulsive High-Order Hopfield Neural Networks

被引：2
|
作者：
Chen, Wei [1 ]
Gong, Shuhua [2 ]
机构：
[1] Shanghai Lixin Univ Commerce, Sch Math & Informat, Shanghai 201620, Peoples R China
[2] Jiaxing Univ, Coll Math Phys & Informat Engn, Jiaxing 314001, Zhejiang, Peoples R China
来源：
ABSTRACT AND APPLIED ANALYSIS | 2014年
关键词：
TIME-VARYING DELAYS; PERIODIC-SOLUTIONS;
D O I：
10.1155/2014/138379
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper is concerned with antiperiodic solutions for impulsive high-order Hopfield neural networks with leakage delays and continuously distributed delays. By employing a novel proof, some sufficient criteria are established to ensure the existence and global exponential stability of the antiperiodic solution, which are new and complement of previously known results. Moreover, an example and numerical simulations are given to support the theoretical result.
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收藏
页数：11
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