Article Abstract

	Title:	Exponential stability of cellular neural networks with time-varying delay
	Author:	Xue-li Wu, Wen-xia Du, Yan-hong Wang, Zhan-tong Zhou
	Address:	Yanshan University, No. 438 Hebei Street, Qinhuangdao, Hebei Province, 066004, P.R. China; College of Electronic Engineering and Information, Hebei University of Science and Technology, No. 70 Yuhua East Road, Shijiazhuang, Hebei Province, 050018, P.R. China. ' Yanshan University, No. 438 Hebei Street, Qinhuangdao, Hebei Province, 066004, P.R. China; Hebei Normal University, No. 113 Yuhua East Road, Shijiazhuang, Hebei Province, 050016, P.R. China. ' College of Electronic Engineering and Information, Hebei University of Science and Technology, No. 70 Yuhua East Road, Shijiazhuang, Hebei Province, 050018, P.R. China. ' College of Electronic Engineering and Information, Hebei University of Science and Technology, No. 70 Yuhua East Road, Shijiazhuang, Hebei Province, 050018, P.R. China
	Journal:	International Journal of Modelling, Identification and Control 2009 - Vol. 8, No.2  pp. 130 - 138
	Abstract:	Time-delay appears frequently in the neural network study, and it is often a source of instability and oscillations in a system. It is very important to research the stability of delayed neural networks, especially for neural networks with time-varying delays. In this paper, a novel method is proposed for the exponential stability of cellular neural networks with time-varying delays. New delay-dependent exponential stability conditions of cellular neural network with time-varying delays are presented by constructing Lyapunov functional and using linear matrix inequality (LMI). Finally, numerical examples are given to demonstrate the effect of the proposed method.
	Keywords:	delayed cellular neural networks; DCNNs; Lyapunov function; linear matrix inequality; LMI; exponential stability; identification; control; time-varying delays; instability; oscillations.
	DOI:	10.1504/IJMIC.2009.029025
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