Further study on finite-time synchronization for delayed inertial neural networks via inequality skills

被引：66
作者：
Zhang, Zhengqiu [1 ]
Chen, Mo [1 ]
Li, Ailing [1 ]
机构：
[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
来源：
NEUROCOMPUTING | 2020年 / 373卷
关键词：
Finite-time synchronization; Delayed master-slave inertial neural networks; Inequality skills; Getting rid of utilizing finite-time synchronization theorems; GLOBAL EXPONENTIAL STABILITY; ANTI-SYNCHRONIZATION; EXISTENCE;
D O I：
10.1016/j.neucom.2019.09.034
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We discuss the finite-time synchronization of a class of delayed inertial neural networks. Getting rid of utilizing some finite-time synchronization theorems and integral inequality skills used in Zhang et al. (2018), by making good use of new inequality skills, two new concise and easily tested criteria to assure the finite-time synchronization for the discussed delayed master-slave inertial neural networks are acquired. The craftsmanship and results of finite-time synchronization for the master-slave neural networks are different from those in some recent works, consequently, our study on the finite-time synchronization of neural networks has definite significance. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：15 / 23
页数：9
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