Passivity analysis of uncertain neural networks with mixed time-varying delays

被引：28

作者：

Kwon, O. M. ^{[1
]}

Park, M. J. ^{[1
]}

Park, Ju H. ^{[2
]}

Lee, S. M. ^{[3
]}

Cha, E. J. ^{[4
]}

机构：

[1] Chungbuk Natl Univ, Sch Elect Engn, Cheongju 361763, South Korea

[2] Yeungnam Univ, Dept Elect Engn, Kyongsan 712749, South Korea

[3] Daegu Univ, Sch Elect Engn, Gyongsan 712714, South Korea

[4] Chungbuk Natl Univ, Sch Med, Dept Biomed Engn, Cheongju 361763, South Korea

来源：

NONLINEAR DYNAMICS | 2013年 / 73卷 / 04期

基金：

新加坡国家研究基金会;

关键词：

Neural networks; Time-varying delays; Passivity; Lyapunov method; MARKOVIAN JUMPING PARAMETERS; ROBUST STABILITY-CRITERIA; EXPONENTIAL STABILITY; DISTRIBUTED DELAYS; ASYMPTOTIC STABILITY; GLOBAL STABILITY; DISCRETE; SYSTEMS; INEQUALITY; DYNAMICS;

D O I：

10.1007/s11071-013-0932-6

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper addresses the passivity problem for uncertain neural networks with both discrete and distributed time-varying delays. It is assumed that the parameter uncertainties are norm-bounded. By construction of an augmented Lyapunov-Krasovskii functional and utilization of zero equalities, improved passivity criteria for the networks are derived in terms of linear matrix inequalities (LMIs) via new approaches. Through three numerical examples, the effectiveness to enhance the feasible region of the proposed criteria is demonstrated.

引用

页码：2175 / 2189

页数：15

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