Exponential Dissipativity of Non-autonomous Neural Networks with Distributed Delays and Reaction-Diffusion Terms

  • Zhiguo Yang
  • Daoyi Xu
  • Yumei Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


In this paper, a class of non-autonomous neural networks with distributed delays and reaction-diffusion terms is considered. Employing the properties of diffusion operator and the techniques of inequality, we investigate positive invariant set, global exponential stability, and then obtain the exponential dissipativity of the neural networks under consideration. Our results can extend and improve earlier ones. An example is given to demonstrate the effectiveness of these results.


Neural Network Recurrent Neural Network Cellular Neural Network Global Exponential Stability Dynamical 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

  • Zhiguo Yang
    • 1
    • 2
  • Daoyi Xu
    • 1
  • Yumei Huang
    • 1
  1. 1.Institute of MathematicsSichuan UniversityChengduChina
  2. 2.College of Mathematics and Software ScienceSichuan Normal UniversityChengduChina

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