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Existence and Global Stability Analysis of Almost Periodic Solutions for Cohen-Grossberg Neural Networks

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Book cover 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, we investigate a large class of periodic Cohen-Grossberg neural networks and prove that under some mild conditions, there is a unique almost-periodic solution, which is globally stable. As special examples, we derive many results given in literature.

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References

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Author information

Authors and Affiliations

  1. Key Laboratory of Nonlinear Science of Educational Chinese Ministry of Education, Institute of Mathematics, Fudan University, Shanghai, 200433, P.R. China

    Tianping Chen, Lili Wang & Changlei Ren

Authors
  1. Tianping Chen
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  2. Lili Wang
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  3. Changlei Ren
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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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Chen, T., Wang, L., Ren, C. (2006). Existence and Global Stability Analysis of Almost Periodic Solutions for Cohen-Grossberg Neural Networks. 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_31

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  • DOI: https://doi.org/10.1007/11759966_31

  • 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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