Finite-time synchronization of delayed competitive neural networks with discontinuous neuron activations

被引：28

作者：

Duan, Lian ^{[1
]}

Fang, Xianwen ^{[1
]}

Yi, Xuejun ^{[2
]}

Fu, Yujie ^{[2
]}

机构：

[1] Anhui Univ Sci & Technol, Sch Math & Big Data, Huainan 232001, Anhui, Peoples R China

[2] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China

来源：

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | 2018年 / 9卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Competitive neural network; Discontinuous activation; Finite-time synchronization; Delayed feedback controller; GLOBAL EXPONENTIAL STABILITY; VARYING DELAYS; SYSTEMS; CONVERGENCE; STABILIZATION;

D O I：

10.1007/s13042-017-0670-z

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the finite-time synchronization problem for a class of delayed competitive neural networks with discontinuous activations. Using the theory of differential inclusions, nonsmooth analysis, inequality techniques and a generalized finite-time convergence theorem, new criteria are established to ensure the finite-time stability of the considered error system, and thus the finite-time synchronization between the drive system and the response system are realized. Finally, two examples with numerical simulations are presented to illustrate the effectiveness of the proposed synchronization criteria.

引用

页码：1649 / 1661

页数：13

共 35 条

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