EXPONENTIAL STABILITY ANALYSIS FOR NEURAL NETWORKS WITH TIME-VARYING DELAY AND LINEAR FRACTIONAL PERTURBATIONS

被引：0
|
作者：
Lien, Chang-Hua [1 ]
Yu, Ker-Wei [1 ]
机构：
[1] Natl Kaohsiung Marine Univ, Dept Marine Engn, Kaohsiung, Taiwan
来源：
JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN | 2014年 / 22卷 / 02期
关键词：
delayed neural network; global exponential stability; delay-dependent criterion; delay-independent criterion; linear fractional perturbation; linear matrix inequality; GLOBAL ROBUST STABILITY; CRITERIA;
D O I：
10.6119/JMST-013-0207-3
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, the global exponential stability and global asymptotic stability for a class of uncertain delayed neural networks (UDNNs) with time-varying delay and linear fractional perturbations are considered. Delay-dependent and delay-independent criteria are proposed to guarantee the robust stability of UDNNs via linear matrix inequality (LMI) approach. Additional nonnegative inequality approach is used to improve the conservativeness of the stability criteria. Some numerical examples are illustrated to show the effectiveness of our results. From the simulation results, significant improvement over the recent results can be observed.
引用
收藏
页码：146 / 153
页数：8
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