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Stochastic Robust Stability of Markovian Jump Nonlinear Uncertain Neural Networks with Wiener Process

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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

This paper deals with the stochastic robust stability problem for Markovian jump nonlinear uncertain neural networks (MJNUNNs) with Wiener process. Some criteria for stochastic robust stability of Markovian jump nonlinear uncertain neural networks are derived, even if the system contains Wiener process. All the derived results are presented in terms of linear matrix inequality.

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Author information

Authors and Affiliations

  1. Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu, 214122, P.R. China

    Xuyang Lou & Baotong Cui

Authors
  1. Xuyang Lou
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  2. Baotong Cui
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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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Lou, X., Cui, B. (2006). Stochastic Robust Stability of Markovian Jump Nonlinear Uncertain Neural Networks with Wiener Process. 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_25

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  • DOI: https://doi.org/10.1007/11759966_25

  • 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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