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On the Domain Attraction of Fuzzy Neural Networks

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Advances in Neural Networks - ISNN 2008 (ISNN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5263))

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Abstract

In this paper, we study qualitative properties of equilibrium points in a class of interval fuzzy neural networks and obtain an estimate on the domain of robust attraction of locally exponentially stable equilibrium points. Both the conditions and the estimate are formulated in terms of the parameter intervals, so they are verifiable easily.

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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 Science and Engineering, Chongqing University, Chongqing, 400030, P.R. China

    Xiaofeng Liao

  3. Fundamental Study Department, Chongqing Logistics and Engineering College,  

    Hui Huang

Authors
  1. Tingwen Huang
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  2. Xiaofeng Liao
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  3. Hui Huang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Huang, T., Liao, X., Huang, H. (2008). On the Domain Attraction of Fuzzy Neural Networks. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87732-5_26

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  • DOI: https://doi.org/10.1007/978-3-540-87732-5_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87731-8

  • Online ISBN: 978-3-540-87732-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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