Exponential stability of cellular neural networks with time-varying delay Online publication date: Tue, 27-Oct-2009
by Xue-li Wu, Wen-xia Du, Yan-hong Wang, Zhan-tong Zhou
International Journal of Modelling, Identification and Control (IJMIC), Vol. 8, No. 2, 2009
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.
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