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The Dahlquist Constant Approach to Stability Analysis of the Static Neural Networks

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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

Avoiding the difficulty of constructing a proper Lyapunov function, the generalized Dahlquist constant approach is employed to investigate the exponential stability of the static neural networks. Without assuming the boundedness, monotonicity of the activations, a new sufficient conditions for existence of an unique equilibrium and the exponential stability of the neural networks are presented. An example is given to show the effectiveness of our results.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Huainan Normal University, Anhui, 232001, China

    Guanjun Li & Jin Xu

Authors
  1. Guanjun Li
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  2. Jin Xu
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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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Li, G., Xu, J. (2009). The Dahlquist Constant Approach to Stability Analysis of the Static Neural Networks. 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_35

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_35

  • 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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