Global exponential convergence of fuzzy cellular neural networks with proportional delays and impulsive effects

被引：9

作者：

Xu, Changjin ^{[1
]}

机构：

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

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2017年 / 33卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Fuzzy cellular neural networks; exponential convergence; proportional delay; impulses; ALMOST-PERIODIC SOLUTIONS; TIME-VARYING DELAYS; DISTRIBUTED DELAYS; VARIABLE-COEFFICIENTS; ASYMPTOTIC STABILITY; LEAKAGE DELAYS; EXISTENCE; SCALES; TERMS;

D O I：

10.3233/JIFS-162279

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, a class of fuzzy cellular neural networks (FCNNs) with proportional delays and impulsive effects are discussed. With the help of the differential inequality theory, a set of sufficient criteria which ensure the global exponential convergence of the fuzzy cellular neural networks with proportional delays and impulsive effects are established. Numerical simulations are conducted to test our theoretical analysis. The results achieved are new and complement some existing works.

引用

页码：969 / 977

页数：9

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