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International Symposium on Neural Networks

ISNN 2006: Advances in Neural Networks - ISNN 2006 pp 93–99Cite as

Exponential Dissipativity of Non-autonomous Neural Networks with Distributed Delays and Reaction-Diffusion Terms

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

Abstract

In this paper, a class of non-autonomous neural networks with distributed delays and reaction-diffusion terms is considered. Employing the properties of diffusion operator and the techniques of inequality, we investigate positive invariant set, global exponential stability, and then obtain the exponential dissipativity of the neural networks under consideration. Our results can extend and improve earlier ones. An example is given to demonstrate the effectiveness of these results.

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References

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Author information

Authors and Affiliations

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

    Zhiguo Yang, Daoyi Xu & Yumei Huang

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

    Zhiguo Yang

Authors
  1. Zhiguo Yang
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  2. Daoyi Xu
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  3. Yumei 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. 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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Cite this paper

Yang, Z., Xu, D., Huang, Y. (2006). Exponential Dissipativity of Non-autonomous Neural Networks with Distributed Delays and Reaction-Diffusion Terms. 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_14

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  • DOI: https://doi.org/10.1007/11759966_14

  • 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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