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

被引：153
|
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
收藏
页码：1476 / 1485
页数：10
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