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A Further Result for Exponential Stability of Neural Networks with Time-Varying 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

This paper focuses on the issue of exponential stability for delayed neural networks with time-varying delays. A further result associated with this issue is exploited by employing a new Lyapunov-Krasovskii functional together with linear matrix inequality technique. Moreover, an approach to estimate the degree of exponential convergence is formulated.

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Author information

Authors and Affiliations

  1. College of Computer Science and Engineering, Chongqing University, 400030, China

    Jun Zhang, Xiaofeng Liao & Chuandong Li

  2. College of Economics Business Administration, Chongqing University, 400030, China

    Anwen Lu

Authors
  1. Jun Zhang
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  2. Xiaofeng Liao
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  3. Chuandong Li
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  4. Anwen Lu
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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, J., Liao, X., Li, C., Lu, A. (2005). A Further Result for Exponential Stability of Neural Networks with Time-Varying 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_18

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  • DOI: https://doi.org/10.1007/11427391_18

  • 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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