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Global Exponential Stability of Delayed Impulsive Hopfield Type Neural Networks

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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

This paper investigate the problems of global exponential stability and exponential convergence rate for delayed impulsive Hopfield type neural networks. By using the method of Lyapunov functions, some sufficient conditions for ensuring global exponential stability of these networks are derived, and the estimate of exponential convergence rate is also obtained. A numerical example is worked out to illustrate the obtained results.

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References

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Author information

Authors and Affiliations

  1. Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China

    Bingji Xu, Yi Shen & **aoxin Liao

  2. College of Information Engineering, China University of Geoscience, Bei**g, 100083, China

    Qun Wang

Authors
  1. Bingji Xu
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  2. Qun Wang
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  3. Yi Shen
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  4. **aoxin Liao
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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

    **aofeng 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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Xu, B., Wang, Q., Shen, Y., Liao, X. (2005). Global Exponential Stability of Delayed Impulsive Hopfield Type Neural Networks. 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_27

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  • DOI: https://doi.org/10.1007/11427391_27

  • 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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