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Global Exponential Stability of T-S Fuzzy Neural Networks with Time-Varying Delays

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Intelligent Computing (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4113))

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Abstract

This paper investigates the global exponential stability of Takagi-Sugeno Fuzzy cellular neural networks with time-varying delays. Using the reduction to absurdity, a less conservative delay-independent stability criterion is derived to guarantee the exponential stability of Takagi-Sugeno Fuzzy cellular neural networks with time-varying delays. Since our model is more general than some existing works, the results presented in this paper are the improvement and extension of the existed ones.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Hubei Normal University, Huangshi, Hubei, 435002, China

    Chaojin Fu

  2. Hubei province Key Laboratory of Bioanalytical Technique, Hubei Normal University,  

    Chaojin Fu

  3. Department of Electric Engineering, ZhongYuan Institute of Technology, Zhengzhou, Henan, 450007, China

    Zhongsheng Wang

Authors
  1. Chaojin Fu
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  2. Zhongsheng Wang
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China

    De-Shuang Huang

  2. Carnegie Mellon University,  

    Kang Li

  3. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Stranmillis Road, BT9 5AH, Belfast, UK

    George William Irwin

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© 2006 Springer-Verlag Berlin Heidelberg

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Fu, C., Wang, Z. (2006). Global Exponential Stability of T-S Fuzzy Neural Networks with Time-Varying Delays. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_44

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  • DOI: https://doi.org/10.1007/11816157_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37271-4

  • Online ISBN: 978-3-540-37273-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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