Periodicity of Cohen-Grossberg-type fuzzy neural networks with impulses and time-varying delays

被引：25

作者：

Meng, Fangru ^{[1
]}

Li, Kelin ^{[1
]}

Song, Qiankun ^{[2
]}

Liu, Yurong ^{[3
,4
]}

Alsaadi, Fuad E. ^{[4
]}

机构：

[1] Sichuan Univ Sci & Engn, Sch Math & Stat, Zigong 643000, Sichuan, Peoples R China

[2] Chongqing Jiaotong Univ, Dept Math, Chongqing 400074, Peoples R China

[3] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China

[4] King Abdulaziz Univ, Fac Engn, Commun Syst & Networks CSN Res Grp, Jeddah 21589, Saudi Arabia

来源：

NEUROCOMPUTING | 2019年 / 325卷

基金：

中国国家自然科学基金;

关键词：

Cohen-Grossberg-type fuzzy neural networks; Impulses; Time-varying delays; Periodic solution; Delay differential inequality; GLOBAL EXPONENTIAL STABILITY; DISCRETE; CRITERIA;

D O I：

10.1016/j.neucom.2018.10.038

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The periodicity problem of a class of Cohen-Grossberg-type fuzzy neural networks with impulses and time-varying delays is concerned in this paper. Via constructing a delay differential inequality, and applying fuzzy theory and the Lyapunov method, several criteria which ensure the existence and exponential stability of the periodic solutions for the considered systems are derived. An example is shown to illustrate the validity of the obtained results. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：254 / 259

页数：6

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