Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time-Varying Delays

被引：1

作者：

Shao, Yuanfu ^{[1
]}

Xu, Changjin ^{[2
]}

Zhang, Qianhong ^{[2
]}

机构：

[1] Guilin Univ Technol, Coll Sci, Guilin 541004, Guangxi, Peoples R China

[2] Guizhou Coll Finance & Econ, Guizhou Key Lab Econ Syst, Guiyang 550004, Guizhou, Peoples R China

来源：

ABSTRACT AND APPLIED ANALYSIS | 2012年

基金：

中国国家自然科学基金;

关键词：

DIFFERENTIAL-EQUATIONS; EXISTENCE; DYNAMICS;

D O I：

10.1155/2012/358362

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

By using Schaeffer's theorem and Lyapunov functional, sufficient conditions of the existence and globally exponential stability of positive periodic solution to an impulsive neural network with time-varying delays are established. Applications, examples, and numerical analysis are given to illustrate the effectiveness of the main results.

引用

页数：14

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