Interval time-varying delay stability for neural networks

被引：9

作者：

Souza, Fernando de Oliveira ^{[2
]}

Palhares, Reinaldo Martinez ^{[1
]}

机构：

[1] Univ Fed Minas Gerais, Dept Elect Engn, BR-31270010 Belo Horizonte, MG, Brazil

[2] Univ Fed Sao Joao del Rei, BR-36420000 Ouro Branco, MG, Brazil

来源：

NEUROCOMPUTING | 2010年 / 73卷 / 13-15期

关键词：

Stability analysis; Neural networks; Interval time-delay; DEPENDENT STABILITY; ASYMPTOTIC STABILITY; CRITERIA;

D O I：

10.1016/j.neucom.2010.04.002

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 presents a new linear matrix inequality (LMI) stability criterion for continuous-time artificial neural networks (ANN) with interval time-varying delay. The varying-time delay is taken as composition of a nominal positive value subject to a time-varying perturbation. The methodology is based on Gu's discretization technique and a strategy that decouples the system matrices from the Lyapunov functional matrices. Two numerical examples are performed to support the theoretical predictions. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：2789 / 2792

页数：4

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