Stability of Inertial Delayed Neural Networks with Impulsive Effect

被引：0
作者：
Qi, Jiangtao [1 ]
Zhang, Wei [2 ]
机构：
[1] Shan Dong Jiaotong Univ, Sch Informat Sci & Elect Engn, Jinan 250357, Shandong, Peoples R China
[2] Southwest Univ, Dept Elect & Informat Engn, Chongqing 400715, Peoples R China
来源：
2017 14TH INTERNATIONAL WORKSHOP ON COMPLEX SYSTEMS AND NETWORKS (IWCSN) | 2017年
关键词：
Inertial neural network; stability; destabilizing impulses; Lyapunov; GLOBAL EXPONENTIAL STABILITY; TIME DELAYS; SYNCHRONIZATION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we investigate the stability problem of a class of inertial delayed neural networks with impulsive effects. We consider the case when both the system state and its first derivation are subjected to the destabilizing impulses, and exploit the stabilization property of destabilizing impulses which can be used to make up for the state divergence caused by unstable inertial delayed neural networks. Based on a new time-dependent Lyapunov function and the comparison principle, some sufficient conditions guaranteeing the exponential stability of the systems are derived.
引用
收藏
页码：347 / 352
页数：6
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