Global asymptotical stability for a class of non-autonomous impulsive inertial neural networks with unbounded time-varying delay

被引:11
|
作者
Li, Hongfei [1 ]
Zhang, Wei [1 ]
Li, Chuandong [1 ]
Zhang, Wanli [1 ]
机构
[1] Southwest Univ, Natl & Local Joint Engn Lab Intelligent Transmiss, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2019年 / 31卷 / 10期
关键词
Global asymptotic stability; Unbounded time-varying delays; Impulse; Inertial neural networks; EXPONENTIAL STABILITY; SYNCHRONIZATION; PERIODICITY; EXISTENCE;
D O I
10.1007/s00521-018-3498-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article is concerned with the global asymptotical stability of non-autonomous impulsive inertial neural networks with unbounded delay. A new impulsive differential delay inequality which involves unbounded and non-differential delay is established. Moreover, based on a new impulsive differential delay inequality, new analysis techniques can effectively avoid the difficulties caused by unbounded delay and impulses, and several novel delay-dependent inequalities are obtained to ensure the global stability of this model. In the end, three examples are given to claim the validity of theoretical analysis.
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页码:6757 / 6766
页数:10
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