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Global Exponential Stability of Fuzzy Cellular Neural Networks with Variable Delays

  • Jiye Zhang
  • Dianbo Ren
  • Weihua Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)

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.

Keywords

Equilibrium Point Exponential Stability Variable Delay Cellular Neural Network Hopfield Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jiye Zhang
    • 1
  • Dianbo Ren
    • 1
  • Weihua Zhang
    • 1
  1. 1.Traction Power State Key LaboratorySouthwest Jiaotong UniversityChengduChina

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