Global Asymptotical Stability in Neutral-Type Delayed Neural Networks with Reaction-Diffusion Terms

  • Jianlong Qiu
  • Jinde Cao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


In this paper, the global uniform asymptotical stability is studied for delayed neutral-type neural networks by constructing appropriate Lyapunov functional and using the linear matrix inequality (LMI) approach. The main condition given in this paper is dependent on the size of the measure of the space, which is usually less conservative than space-independent ones. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed criteria.


Neural Network Linear Matrix Inequality Exponential Stability Recurrent Neural Network Cellular 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

  • Jianlong Qiu
    • 1
    • 2
  • Jinde Cao
    • 1
  1. 1.Department of MathematicsSoutheast UniversityNanjingChina
  2. 2.Department of MathematicsLinyi Normal UniversityLinyiChina

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