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Global Attractivity of Cohen-Grossberg Model with Delays

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

In this paper, we have studied the global attractivity of the equilibrium of Cohen-Grossgerg model with both finite and infinite delays. Criteria for global attractivity are also derived by means of Lyapunov functionals. As a corollary, we show that if the delayed system is dissipative and the coefficient matrix is VL-stable, then the global attractivity of the unique equilibrium is maintained provided the delays are small. Estimates on the allowable sizes of delays are also given. Applications to the Hopfield neural networks with discrete delays are included.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Chongqing University, Chongqing, 400044, China

    Tao Xiang & Xiaofeng Liao

  2. Department of Automation, Chongqing University,  

    Jian Huang

Authors
  1. Tao Xiang
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  2. Xiaofeng Liao
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  3. Jian Huang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Xiang, T., Liao, X., Huang, J. (2005). Global Attractivity of Cohen-Grossberg Model with Delays. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_35

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  • DOI: https://doi.org/10.1007/11427391_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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