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On Equilibrium and Stability of a Class of Neural Networks with Mixed Delays

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3971))

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Abstract

In this paper the authors analyze problems of existence and global asymptotic stability of the equilibrium for the neural networks with mixed delays. Some new sufficient conditions ensuring the existence, uniqueness, and global asymptotic stability of the equilibrium are established by means of Leray-Schauder principle, arithmetic-mean-geometric-mean inequality and vector delay differential inequality technique. These conditions are less restrictive than previously known criteria.

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References

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Author information

Authors and Affiliations

  1. College of Mathematics and Software Science, Sichuan Normal University, Chengdu, 610066, China

    Shuyong Li

  2. Institute of Mathematics, Sichuan University, Chengdu, 610064, China

    Yumei Huang & Daoyi Xu

  3. School of Mathematics and Computer Engineering, Xihua university, Pixian, 610039, China

    Yumei Huang

Authors
  1. Shuyong Li
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  2. Yumei Huang
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  3. Daoyi Xu
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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. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Li, S., Huang, Y., Xu, D. (2006). On Equilibrium and Stability of a Class of Neural Networks with Mixed Delays. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_21

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  • DOI: https://doi.org/10.1007/11759966_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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