Global exponential convergence analysis of delayed cellular neural networks
Zhang Qiang (张 强)a, Ma Run-Nian (马润年)a, Wang Chao (王 超)a, Xu Jin (许 进)b
a Institute of Electronic Engineering, Xidian University, Xi'an 710071, China; b Institute of System Science, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract Some sufficient criteria have been established to ensure the global exponential stability of delayed cellular neural networks by using an approach based on delay differential inequality. Compared with the method of Lyapunov functionals as in most previous studies, our method is simpler and more effective for a stability analysis of delayed system. Some previously established results in the literature are shown to be special cases of the present result.
Received: 26 February 2002
Revised: 06 July 2002
Accepted manuscript online:
Fund: Project supported by the National Natural Science Foundation of China (Grant No 69971018).
Cite this article:
Zhang Qiang (张 强), Ma Run-Nian (马润年), Wang Chao (王 超), Xu Jin (许 进) Global exponential convergence analysis of delayed cellular neural networks 2003 Chinese Physics 12 22
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