Robust exponential stability analysis for delayed neural networks with time-varying delay

被引：0
作者：
Jing-Chen Xie
Chin-Pin Chen
Pin-Lin Liu
Yoau-Chau Jeng
机构：
[1] Far East University,Department of Digital Media Design and Management
[2] National Changhua University of Education,Department of Industrial Education and Technology
[3] Chienkuo Technology University,Department of Automation Engineering, Institute of Mechatronoptic Systems
来源：
Advances in Difference Equations | / 2014卷
关键词：
exponential stability; linear matrix inequality (LMI); neural networks; time-varying delay;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper considers the problems of determining the robust exponential stability and estimating the exponential convergence rate for delayed neural networks with parametric uncertainties and time delay. The relationship among the time-varying delay, its upper bound, and their difference is taken into account. Theoretic analysis shows that our result includes a previous result derived in the literature. As illustrations, the results are applied to several concrete models studied in the literature, and a comparison of results is given.
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