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Existence and Global Attractivity of Stable Solutions in Neural Networks

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  • Patrick Leoni
  • Pietro Senesi

Abstract

The present paper shows that a su�cient condition for the existence of a stable solution to an autoregressive neural network model is the continuity and boundedness of the activation function of the hidden units in the multi layer perceptron (MLP). In addition, uniqueness of a stable solution is ensured by global lipschitzness and some conditions on the parameters of the system. In this case, the stable value is globally stable and convergence of the learning process occurs at exponential rate.

Suggested Citation

  • Patrick Leoni & Pietro Senesi, "undated". "Existence and Global Attractivity of Stable Solutions in Neural Networks," IEW - Working Papers 198, Institute for Empirical Research in Economics - University of Zurich.
    • Handle: RePEc:zur:iewwpx:198
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    File URL: https://www.zora.uzh.ch/id/eprint/52093/1/iewwp198.pdf
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    Cited by:

    1. Bruno S. Frey & Simon Luechinger & Alois Stutzer, 2007. "Calculating Tragedy: Assessing The Costs Of Terrorism," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 1-24, February.

    More about this item

    Keywords

    Neural Networks; Stable Value;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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