Globally exponential stability conditions for cellular neural networks with time-varying delays

Authors:
Dongming Zhou;Jinde Cao
Affiliations:
Information College, Yunnan University, Kunming 650091, China;Department of Applied Mathematics, Southeast University, Nanjing 210096, China
Venue:
Applied Mathematics and Computation
Year:
2002

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Abstract

In this paper, the problems of global exponential stability for cellular neural networks (CNN) with time-varying delays are studied. Several sufficient conditions guaranteeing the network's global exponential stability are established. These results can easily be used to design and verify globally stable networks. Furthermore, the results presented here are independent of the form of specific delays and have important significance in both theory and applications.