Global Stability of Bidirectional Associative Memory Neural Networks with Variable Coefficients and S-Type Distributed Delays

  • Yonggui Kao
  • Cunchen Gao
  • Lu Wu
  • Qinghe Ming
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4232)


This paper is devoted to investigation of the global asymptotic stability for Bidirectional associative memory (BAM) neural networks with variable coefficient and S-type distributed signal transmission delays along the axon of a neuron. Some sufficient conditions for global asymptotic stability of the networks was obtained, in which the boundedness and differentiability of the signal functions in some papers are deleted. Some examples are also presented to show that our results are new and improve the previous results.


Neural Network Exponential Stability Global Stability Unique Equilibrium Global Asymptotic Stability 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yonggui Kao
    • 1
  • Cunchen Gao
    • 2
  • Lu Wu
    • 1
  • Qinghe Ming
    • 3
  1. 1.College of Information Science and EngineeringOcean University of ChinaQingdaoP.R. China
  2. 2.Department of MathematicsOcean University of ChinaQingdaoP.R. China
  3. 3.Department of MathematicsZaoZhuang UniversityP.R. China

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