Improved passivity analysis for neural networks with Markovian jumping parameters and interval time-varying delays

被引：29

作者：

Chen, Guoliang ^{[1
]}

Xia, Jianwei ^{[1
]}

Zhuang, Guangming ^{[1
]}

机构：

[1] Liaocheng Univ, Sch Math Sci, Liaocheng 252000, Peoples R China

来源：

NEUROCOMPUTING | 2015年 / 155卷

基金：

中国国家自然科学基金;

关键词：

Neural networks; Passivity; Interval time-varying delays; Markovian jumping parameters; EXPONENTIAL STABILITY; DEPENDENT STABILITY; ASYMPTOTIC STABILITY; NEUTRAL-TYPE; CRITERIA; DISCRETE; SYSTEMS;

D O I：

10.1016/j.neucom.2014.12.023

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The problem of passivity analysis for neural networks with Markovian jumping parameters and interval time-varying delays is investigated in this paper. By constructing a novel Lyapunov-Krasovskii functional based on the complete delay-decomposing idea and using reciprocally convex technique, some improved delay-dependent passivity criteria are established in terms of linear matrix inequalities. Numerical examples are also given to show the effectiveness of the proposed methods. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：253 / 260

页数：8

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