Global exponential stability and periodic solutions of cellular neural networks with delay.
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.
Fang
H
H
Center for Nonlinear Science Studies, Kunming University of Science and Technology, Kunming 650093, People's Republic of China. huifangkm@ynmail.com
Li
J
J
D000818:Animals; D055592:Biophysical Phenomena; D001703:Biophysics; D006801:Humans; D008959:Models, Neurological; D008962:Models, Theoretical; D009415:Nerve Net / Q000502:physiology*; D010507:Periodicity