H∞ stability conditions for delayed neural networks with external disturbances and norm-bounded uncertainties: Delay independent and dependent criteria

被引：2

作者：

Ahn, Choon Ki ^{[1
]}

机构：

[1] Seoul Natl Univ Sci & Technol, Dept Automot Engn, Seoul 139743, South Korea

来源：

SCIENCE CHINA-INFORMATION SCIENCES | 2011年 / 54卷 / 08期

关键词：

H-infinity analysis; delayed neural networks; uncertainty; disturbance; linear matrix inequality (LMI); GLOBAL ASYMPTOTIC STABILITY; ROBUST STABILITY; TIME DELAYS;

D O I：

10.1007/s11432-011-4282-z

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we propose new delay independent and dependent H (a) stability conditions for delayed neural networks with external disturbances and norm-bounded uncertainties. These conditions are presented to not only guarantee the asymptotical stability but also reduce the effect of external disturbance to an H (a) norm constraint. The proposed conditions are represented by linear matrix inequalities (LMIs). Optimal H (a) norm bounds are obtained easily by solving convex problems in terms of LMIs. The applicability of these conditions is illustrated by numerical examples.

引用

页码：1691 / 1701

页数：11

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