Finite-Time Stability of Neural Networks with Impulse Effects and Time-Varying Delay

被引：17
作者：
Tan, Jie [1 ,2 ]
Li, Chuandong [1 ]
机构：
[1] Southwest Univ, Chongqing Key Lab Nonlinear Circuits & Intelligen, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China
[2] Chongqing Univ Sci & Technol, Coll Math & Phys, Chongqing 401331, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2017年 / 46卷 / 01期
关键词：
Finite-time; Impulsive effects; Time-varying delay; COMPLEX DYNAMICAL NETWORKS; SUFFICIENT CONDITIONS; MULTIAGENT SYSTEMS; PERIODIC-SOLUTIONS; SYNCHRONIZATION; STABILIZATION; CONSENSUS; DISCRETE;
D O I：
10.1007/s11063-016-9570-6
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, the impulsive effects on the finite-time stability of neural networks with time-varying delay are considered. Several novel criteria which govern the systems considered are finite-time stable are obtained by the idea of Lyapunov-Krasovskii functional and the average impulsive interval method. Moreover, the proposed sufficient conditions can be simplified into the form of linear matrix equalities which can be easily checked by Matlab LMI toolbox. The results proposed show that the model can achieve stable in finite time with stabilizing impulsive effects on one hand, and it can preserve the finite-time stability property in presence of destabilizing impulses on the other hand. Numerical examples are presented to demonstrate the effectiveness of the obtained results.
引用
收藏
页码：29 / 39
页数：11
相关论文
共 35 条
[1]   Necessary and sufficient conditions for finite-time stability of impulsive dynamical linear systems [J].
Amato, F. ;
De Tommasi, G. ;
Pironti, A. .
AUTOMATICA, 2013, 49 (08) :2546-2550
[2]   Finite-time synchronization of Markovian jump complex networks with partially unknown transition rates [J].
Cui, Wenxia ;
Sun, Shaoyuan ;
Fang, Jian-an ;
Xu, Yulong ;
Zhao, Lingdong .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2014, 351 (05) :2543-2561
[3]   Generalized Lyapunov approach for convergence of neural networks with discontinuous or non-Lipschitz activations [J].
Forti, A ;
Grazzini, A ;
Nistri, P ;
Pancioni, L .
PHYSICA D-NONLINEAR PHENOMENA, 2006, 214 (01) :88-99
[4]   A Recurrent Neural Network for Solving Bilevel Linear Programming Problem [J].
He, Xing ;
Li, Chuandong ;
Huang, Tingwen ;
Li, Chaojie ;
Huang, Junjian .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (04) :824-830
[5]   Finite time stability of nonlinear impulsive systems and its applications in sampled-data systems [J].
Lee, Liming ;
Liu, Yang ;
Liang, Jinling ;
Cai, Xiushan .
ISA TRANSACTIONS, 2015, 57 :172-178
[6]   A Three-Parameter S-Shaped Function of Flood Return Period and Damage [J].
Li, Chaochao ;
Cheng, Xiaotao ;
Li, Na ;
Liang, Zhongmin ;
Wang, Yanyan ;
Han, Song .
ADVANCES IN METEOROLOGY, 2016, 2016
[7]   A Generalized Hopfield Network for Nonsmooth Constrained Convex Optimization: Lie Derivative Approach [J].
Li, Chaojie ;
Yu, Xinghuo ;
Huang, Tingwen ;
Chen, Guo ;
He, Xing .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (02) :308-321
[8]   Second-Order Locally Dynamical Consensus of Multiagent Systems With Arbitrarily Fast Switching Directed Topologies [J].
Li, Huaqing ;
Liao, Xiaofeng ;
Huang, Tingwen .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2013, 43 (06) :1343-1353
[9]   Second-Order Consensus Seeking in Multi-Agent Systems With Nonlinear Dynamics Over Random Switching Directed Networks [J].
Li, Huaqing ;
Liao, Xiaofeng ;
Lei, Xinyu ;
Huang, Tingwen ;
Zhu, Wei .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2013, 60 (06) :1595-1607
[10]   Impulsive differential equations: Periodic solutions and applications [J].
Li, Xiaodi ;
Bohner, Martin ;
Wang, Chuan-Kui .
AUTOMATICA, 2015, 52 :173-178
1234