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Global Exponential Stability of Equilibrium Point of Hopfield Neural Network with Delay

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Advances in Neural Networks - ISNN 2010 (ISNN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6063))

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Abstract

In this paper, the global exponential stability of the Hopfield neural network with delay is studied. By using of the methods of constant variation and variable substitution, a new sufficient global exponential stable criterion for the equilibrium point of the network is derived. The result is different to the known references and is realizable easily.

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References

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Author information

Authors and Affiliations

  1. College of Aeronautical Automation, Civil Aviation University of China, TianJin, 300300, China

    Xiaolin Liu

  2. College of Astronautics, Northwestern Polytechnical University, XiAn, 710072, China

    Kun Yuan

Authors
  1. Xiaolin Liu
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  2. Kun Yuan
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Liqing Zhang

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, 200240, Shanghai, China

    Bao-Liang Lu

  3. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water bay, Kowloon, Hong Kong, China

    James Kwok

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© 2010 Springer-Verlag Berlin Heidelberg

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Liu, X., Yuan, K. (2010). Global Exponential Stability of Equilibrium Point of Hopfield Neural Network with Delay. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13278-0_70

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  • DOI: https://doi.org/10.1007/978-3-642-13278-0_70

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13277-3

  • Online ISBN: 978-3-642-13278-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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