Lagrange stability analysis for complex-valued neural networks with leakage delay and mixed time-varying delays

被引:77
|
作者
Song, Qiankun [1 ]
Shu, Hanqi [2 ]
Zhao, Zhenjiang [3 ]
Liu, Yurong [4 ,5 ]
Alsaadi, Fuad E. [5 ]
机构
[1] Chongqing Jiaotong Univ, Dept Math, Chongqing 400074, Peoples R China
[2] Chongqing Jiaotong Univ, Sch Econ & Management, Chongqing 400074, Peoples R China
[3] Huzhou Univ, Dept Math, Huzhou 313000, Peoples R China
[4] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China
[5] King Abdulaziz Univ, Fac Engn, Commun Syst & Networks CSN Res Grp, Jeddah 21589, Saudi Arabia
基金
中国国家自然科学基金;
关键词
Complex-valued neural networks; Lagrange stability; Time-varying discrete delays; Time-varying distributed delays; Leakage delay; Linear matrix inequality in complex domain; GLOBAL EXPONENTIAL STABILITY; GENERAL ACTIVATION FUNCTIONS; ASSOCIATIVE MEMORY; DISTRIBUTED DELAYS; STATE ESTIMATION; NEUTRAL TYPE; DISCRETE; SENSE; DYNAMICS;
D O I
10.1016/j.neucom.2017.03.015
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper discusses the stability in Lagrange sense for complex-valued neural networks with time varying discrete delays and distributed delays as well as leakage delay. By constructing an appropriate Lyapunov-Krasovskii functional, and employing free-weighting-matrix approach and inequality techniques in matrix form, a sufficient criterion to guarantee global exponential stability in Lagrange sense is obtained for the investigated neural networks. The given criterion is delay-dependent and is shown as linear matrix inequalities in complex domain, which can be calculated numerically applying valid YALMIP toolbox in MATLAB. A numerical example is provided to manifest the validity of the proposed result. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:33 / 41
页数:9
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