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Further Stability Analysis for Neural Networks with Time-Varying Interval Delay

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Book cover Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5551))

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Abstract

This paper provides improved results on stability condition for a class of neural networks (NNs) with time-varying interval delay. The activation functions of the NNs are assumed to be more general. Based on a new augmented Lyapunov-Krasovskii functional, the improved delay-dependent stability criterion for delay NNs is obtained in terms of linear matrix inequalities (LMIs). It is shown that the new criterion can provide less conservative results than some existing ones. A numerical example is given to demonstrate the effectiveness and the benefits of the proposed method.

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Authors and Affiliations

  1. School of Information Science and Technology, Yancheng Teachers University, Yancheng, 224002, China

    Qiufeng Cai & Jianjiang Yu

Authors
  1. Qiufeng Cai
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  2. Jianjiang Yu
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, Rapid City, SD 57701, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Cai, Q., Yu, J. (2009). Further Stability Analysis for Neural Networks with Time-Varying Interval Delay. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_49

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01506-9

  • Online ISBN: 978-3-642-01507-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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