Fixed-time synchronization of discontinuous fuzzy competitive neural networks via quantized control

被引：15

作者：

Zheng, Caicai ^{[1
,2
]}

Yu, Juan ^{[1
,2
]}

Kong, Fanchao ^{[3
]}

Hu, Cheng ^{[1
,2
]}

机构：

[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830017, Peoples R China

[2] Xinjiang Key Lab Appl Math XJDX1401, Urumqi 830017, Peoples R China

[3] Anhui Normal Univ, Sch Math & Stat, Wuhu 241000, Peoples R China

来源：

FUZZY SETS AND SYSTEMS | 2024年 / 482卷

基金：

中国国家自然科学基金;

关键词：

Fuzzy competitive neural network; Quantized control; Fixed-time synchronization; Time-varying delay; Discontinuous activation; GLOBAL EXPONENTIAL STABILITY; DELAYS;

D O I：

10.1016/j.fss.2024.108913

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This article concentrates on fixed -time synchronization for discontinuous fuzzy competitive neural networks including time -varying delays. Firstly, to cut down the signal transmission cost, two kinds of nontrivial control strategies, namely quantized control protocols without the linear part, are developed to investigate fixed -time synchronization of discontinuous fuzzy competitive neural networks based on two different types of Lyapunov functions. Then, with the aid of inequality skills and differential inclusion theory, several uncomplicated synchronization criteria are attained and the synchronized time possessing less conservativeness is effectively evaluated. A numerical example is presented at last to testify the validity of theoretical analysis.

引用

页数：19

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