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A multilayer real-time, recurrent learning algorithm for improved convergence

  • Part III: Learning: Theory and Algorithms
  • Conference paper
  • First Online:
Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

In this paper an algorithm is described, which is based on the Real-Time Recurrent Learning (RTRL) algorithm by Williams and Zipser

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References

  1. R.J. Williams and D. Zipser. Experimental Analysis of the Real-Time Recurrent Learning Algorithm. Connection Science, (1), 87–111, 1989.

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Author information

Authors and Affiliations

  1. Expert Systems Applications Development Group, Dept. of Chemical Engineering, K.U.Leuven, De Croylaan 46, 3001, Heverlee, Belgium

    Kürt Meert

  2. Department of Computer Science, University of Stellenbosch, 7602, Stellenbosch, South Africa

    Jacques Ludik

Authors
  1. Kürt Meert
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  2. Jacques Ludik
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Meert, K., Ludik, J. (1997). A multilayer real-time, recurrent learning algorithm for improved convergence. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020195

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  • DOI: https://doi.org/10.1007/BFb0020195

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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