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Exponential Stability Analysis of Neural Networks with Multiple Time Delays

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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

Without assuming the boundedness, strict monotonicity and differentiability of the activation function, a result is established for the global exponential stability of a class of neural networks with multiple time delays. A new sufficient condition guaranteeing the uniqueness and global exponential stability of the equilibrium point is established. The new stability criterion imposes constraints, expressed by a linear matrix inequality, on the self-feedback connection matrix and interconnection matrices independent of the time delays. The stability criterion is compared with some existing results, and it is found to be less conservative than existing ones.

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Author information

Authors and Affiliations

  1. Northeastern University, Shenyang, Liaoning, 110004, China

    Huaguang Zhang & Zhanshan Wang

  2. Shenyang Ligong University, Shenyang, Liaoning, 110045, P.R. China

    Zhanshan Wang

  3. University of Illinois, Chicago, IL, 60607-7053, USA

    Derong Liu

Authors
  1. Huaguang Zhang
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  2. Zhanshan Wang
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  3. Derong Liu
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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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Zhang, H., Wang, Z., Liu, D. (2005). Exponential Stability Analysis of Neural Networks with Multiple Time Delays. 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_21

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  • DOI: https://doi.org/10.1007/11427391_21

  • 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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