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Issue:Generalized net model of backpropagation learning algorithm

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Title of paper: Generalized net model of backpropagation learning algorithm
Maciej Krawczak
Systems Research Institute - Polish Academy of Sciences, Warsaw, Poland
Wyzsza Szkola Informatyki Stosowanej i Zarzadzania
Hristo Aladjov
CLBME - Bulg. Academy of Sciences, Acad. G. Bonchev Str., 105 Block, Sofia-1113, Bulgaria
Presented at: 3rd IWGN, Sofia, 1 October 2002
Published in: Conference proceedings, pages 32—36
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Abstract: The backpropagation algorithm and its modifications are frequently used approaches for feed-forward neural networks training. It is shown in the present paper how generalized net model [1,2] of pure backpropagation algorithm can be constructed. The basic idea of this model is to be used as frame in which, with minor changes different algorithm definitions can be introduced, tested and compared.
Keywords: Generalized nets, Neural networks, Machine learning, Backpropagation
  1. Atanassov K., Generalized Nets, World Scientific, Singapore, 1991.
  2. Atanassov K., Generalized index matrices, Comptes rendus de l'Academie Bulgare des Sciences, vol.40, 1987, No.11, 15-18.
  3. Atanassov, K., 1998. Generalized Nets in Artificial Intelligence. Vol. 1: Generalized nets and Expert Systems. "Prof. M. Drinov" Academic Publishing House, Sofia.
  4. Atanassov K., Aladjov, H., 2000. Generalized nets in artificial intelligence. Vol. 2, "Prof. Marin Drinov" Academic Publishing House, Sofia.

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