Finite-Time Stability of Nonlinear Impulsive Systems With Applications to Neural Networks

被引:30
作者
Yang, Xueyan [1 ]
Li, Xiaodi [2 ]
机构
[1] Shandong Normal Univ, Sch Math & Stat, Jinan 250014, Peoples R China
[2] Shandong Normal Univ, Ctr Control & Engn Computat, Jinan 250014, Peoples R China
基金
中国国家自然科学基金;
关键词
Neural networks; Asymptotic stability; Delay effects; Stability criteria; State estimation; Switches; Mathematical model; Delay-dependent impulse; finite-time contractive stability (FTCS); finite-time stability (FTS); neural networks; nonlinear impulsive systems; LYAPUNOV CONDITIONS; DELAYED-IMPULSES; STATE ESTIMATION;
D O I
10.1109/TNNLS.2021.3093418
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 studies the problem of finite-time stability (FTS) and finite-time contractive stability (FTCS) for nonlinear impulsive systems, where the possibility of time delay in impulses is fully considered. Some sufficient conditions for FTS/FTCS are constructed in the framework of Lyapunov function methods. A relationship between impulsive frequency and the time delay existing in impulses is established to reveal FTS/FTCS performance. As an application, we apply the theoretical results to finite-time state estimation of neural networks, including time-varying neural networks and switched neural networks. Finally, two illustrated examples are given to show the effectiveness and distinctiveness of the proposed delay-dependent impulsive schemes.
引用
收藏
页码:243 / 251
页数:9
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