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Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Delay

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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

In this paper, we investigate the exponential stability of fuzzy cellular networks with unbounded delay. An easily verified sufficient condition is obtained. Moreover, we get the exponential convergent rate for a broad class of the unbounded delayed fuzzy cellular networks.

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Author information

Authors and Affiliations

  1. Texas A&M University at Qatar, Doha, P. O. Box 5825, Qatar

    Tingwen Huang

  2. Department of Computer and Engineering, Chongqing University, Chongqing, 400044, China

    Linhua Zhang

Authors
  1. Tingwen Huang
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  2. Linhua Zhang
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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

    Xiaofeng 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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Huang, T., Zhang, L. (2005). Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Delay. 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_25

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  • DOI: https://doi.org/10.1007/11427391_25

  • 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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