Global exponential stability of fuzzy cellular neural networks with variable delays

Authors:
Jiye Zhang;Dianbo Ren;Weihua Zhang
Affiliations:
Traction Power State Key Laboratory, Southwest Jiaotong University, Chengdu, China;Traction Power State Key Laboratory, Southwest Jiaotong University, Chengdu, China;Traction Power State Key Laboratory, Southwest Jiaotong University, Chengdu, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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Abstract

In this paper, the global exponential stability of fuzzy cellular neural networks with time-varying delays is studied. Without assuming the boundedness and differentiability of the activation functions, based on the properties of M-matrix, by constructing vector Liapunov functions and applying differential inequalities, the sufficient conditions ensuring existence, uniqueness, and global exponential stability of the equilibrium point of fuzzy cellular neural networks with variable delays are obtained.