Passivity analysis of neural networks with two different Markovian jumping parameters and mixed time delays

被引：5

作者：

Ren, Jiaojiao ^{[1
,2
]}

Liu, Xinzhi ^{[2
]}

Zhu, Hong ^{[1
]}

Zhong, Shouming ^{[3
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Peoples R China

[2] Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada

[3] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China

来源：

ISA TRANSACTIONS | 2017年 / 69卷

基金：

中国国家自然科学基金; 加拿大自然科学与工程研究理事会;

关键词：

Passivity analysis; Markovian jumping parameters; Leakage delay; Neural networks; STATE ESTIMATION; NEUTRAL TYPE; H-INFINITY; DISCRETE; STABILITY; SYNCHRONIZATION;

D O I：

10.1016/j.isatra.2017.04.001

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 studies the problem of passivity analysis for neural networks with two different Markovian jumping parameters and mixed time delays utilizing some integral inequalities. The integral inequalities produce sharper bounds than what the Jensen's inequality produces, consequently, better results are obtained. The Markovian jumping parameters in connection weight matrices and discrete delay are assumed to be different in the system model. By constructing a new appropriate Lyapunov-Krasovskii functional (LKF), some sufficient conditions are established which guarantee the passivity of the proposed model. Numerical examples are given to show the less conservatism and effectiveness of the proposed method. (C) 2017 ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：102 / 121

页数：20

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