Novel Finite-Time Synchronization Criteria for Inertial Neural Networks With Time Delays via Integral Inequality Method

被引：160

作者：

Zhang, Zhengqiu ^{[1
]}

Cao, Jinde ^{[2
,3
]}

机构：

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

[2] Southeast Univ, Jiangsu Prov Key Lab Networked Collect Intelligen, Nanjing 210096, Jiangsu, Peoples R China

[3] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2019年 / 30卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Finite-time stability; finite-time synchronization; inertial neural networks; integral inequality; PERIODIC-SOLUTIONS; STABILITY; CONTROLLERS;

D O I：

10.1109/TNNLS.2018.2868800

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, we are concerned with the finite-time synchronization of a class of inertial neural networks with time delays. Without applying some finite-time stability theorems, which are widely applied to studying the finite-time synchronization for neural networks, by constructing two Lyapunov functions and using integral inequality method, two sufficient conditions on the finite-time synchronization for a class of inertial neural networks with time delays are derived. Considering that the method and research results of the finite-time synchronization are different from some existing works, this paper extends the works on the finite-time synchronization of neural networks.

引用

页码：1476 / 1485

页数：10

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