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Robust Stability of Interval Delayed Neural Networks

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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

Recently, there are several papers discussing global robust stability of the equilibrium point for the interval delayed neural networks. However, we find these criteria are not accurate. In this paper, based on Linear Matrix Inequality (LMI) technique, we propose an algorithm to determine in which region the interval delayed system is globally robust stabile. This approach is much more powerful than the criteria given in previous papers. We also give a numerical example to illustrate the viability of our algorithm.

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References

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Author information

Authors and Affiliations

  1. Laboratory of Nonlinear Science, Institute of Mathematics, Fudan University, Shanghai, 200433, China

    Wenlian Lu & Tianping Chen

Authors
  1. Wenlian Lu
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  2. Tianping Chen
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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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Lu, W., Chen, T. (2005). Robust Stability of Interval Delayed Neural Networks. 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_33

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  • DOI: https://doi.org/10.1007/11427391_33

  • 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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