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

Advances in Difference Equations

Yoau-Chau Jeng¹  Jing-Chen Xie²  Chin-Pin Chen³  Pin-Lin Liu³ 

[1] Department of Automation Engineering, Institute of Mechatronoptic Systems, Chienkuo Technology University, Changhua, ROC;Department of Digital Media Design and Management, Far East University, Tainan, ROC;Department of Industrial Education and Technology, National Changhua University of Education, Changhua, ROC

关键词: exponential stability;    linear matrix inequality (LMI);    neural networks;    time-varying delay;   

DOI  :  10.1186/1687-1847-2014-131

学科分类：数学（综合）

来源: SpringerOpen

【 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.

【 授权许可】

CC BY