On almost automorphic solutions for cellular neural networks with time-varying delays in leakage terms on time scales

被引：19

作者：

Xu, Changjin ^{[1
]}

Wu, Yusen ^{[2
]}

机构：

[1] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550004, Peoples R China

[2] Henan Univ Sci & Technol, Sch Math & Stat, Luoyang, Peoples R China

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2016年 / 30卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Cellular neural networks; almost automorphic solution; exponential stability; leakage term; time-varying delay; ALMOST-PERIODIC SOLUTIONS; ANTIPERIODIC SOLUTIONS; EXPONENTIAL STABILITY; GLOBAL STABILITY; DYNAMIC EQUATIONS; MILD SOLUTIONS; EXISTENCE;

D O I：

10.3233/IFS-151766

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, cellular neural networks(CNNs) with time-varying leakage delays on time scales are investigated. By applying the existence of the exponential dichotomy of linear dynamic equations on time scales, fixed point theorem and the theory of calculus on time scales, a set of sufficient conditions are obtained for the existence and exponential stability of almost automorphic solutions for the model. An example with its numerical simulations is given to illustrate the feasibility and effectiveness of the obtained results.

引用

页码：423 / 436

页数：14