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.
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页数：14
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