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Stability Analysis of Reaction-Diffusion Recurrent Cellular Neural Networks with Variable Time Delays

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

Abstract

In this paper, the global exponential stability of a class of recurrent cellular neural networks with reaction-diffusion and variable time delays was studied. When neural networks contain unbounded activation functions, it may happen that equilibrium point does not exist at all. In this paper, without assuming the boundedness, monotonicity and differentiability of the active functions, the algebraic criteria ensuring existence, uniqueness and global exponential stability of the equilibrium point of neural networks are obtained.

Keywords

Neural Network Equilibrium Point 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

  • Weifan Zheng
    • 1
  • Jiye Zhang
    • 1
  • Weihua Zhang
    • 1
  1. 1.Traction Power State Key LaboratorySouthwest Jiaotong UniversityChengduChina

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