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Global exponential stability and periodic solutions of cellular neural networks with delay
1Center for Nonlinear Science Studies, Kunming University of Science and Technology, Kunming 650093, People's Republic of China. huifangkm@ynmail.com
Abstract:
In this paper, some sufficient conditions for the global exponential stability and the existence of periodic solutions of cellular neural networks with delay (DCNN) model are obtained by means of a Lyapunov functional approach. These conditions can be used to design globally stable DCNN's and periodic oscillatory DCNN's and thus have important significance in both theory and applications.