Passivity analysis of memristor-based impulsive inertial neural networks with time-varying delays

被引:42
|
作者
Wan, Peng [1 ]
Jian, Jigui [1 ]
机构
[1] China Three Gorges Univ, Coll Sci, Yichang 443002, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Memristor; Inertial neural network; Passivity; Time-varying delay; Impulse; GLOBAL EXPONENTIAL STABILITY; STABILIZATION; SYNCHRONIZATION; SYSTEMS; CHAOS;
D O I
10.1016/j.isatra.2018.02.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper focuses on delay-dependent passivity analysis for a class of memristive impulsive inertial neural networks with time-varying delays. By choosing proper variable transformation, the memristive inertial neural networks can be rewritten as first-order differential equations. The memristive model presented here is regarded as a switching system rather than employing the theory of differential inclusion and set-value map. Based on matrix inequality and Lyapunov-Krasovskii functional method, several delay-dependent passivity conditions are obtained to ascertain the passivity of the addressed networks. In addition, the results obtained here contain those on the passivity for the addressed networks without impulse effects as special cases and can also be generalized to other neural networks with more complex pulse interference. Finally, one numerical example is presented to show the validity of the obtained results. (C) 2018 ISA Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:88 / 98
页数:11
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