Global Exponential Stability of Fuzzy Cohen-Grossberg Neural Networks with Variable Delays and Distributed Delays

Authors:
Jiye Zhang;Dianbo Ren;Weihua Zhang
Affiliations:
Traction Power State Key Laboratory, Southwest Jiaotong University, Chengdu 610031, China;Traction Power State Key Laboratory, Southwest Jiaotong University, Chengdu 610031, China;Traction Power State Key Laboratory, Southwest Jiaotong University, Chengdu 610031, China
Venue:
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Year:
2009

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Abstract

In this paper, we extend the Cohen---Grossberg neural networks from classical to fuzzy sets, and propose the fuzzy Cohen---Grossberg neural networks (FCGNN). The global exponential stability of FCGNN with variable delays and distributed delays is studied. 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 Cohen---Grossberg neural networks with variable delays and distributed delays are obtained.