Issue:Modeling the algorithm backpropagation for learning of neural networks with generalized nets. Part 1

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Title of paper: Modeling the algorithm backpropagation for learning of neural networks with generalized nets. Part 1 Author(s): Sotir Sotirov University “Prof. D-r Assen Zlatarov” – Bourgas, Bulgaria ssotirov@btu.bg Presented at: 4th IWGN, Sofia, 23 September 2003 Published in: Conference proceedings, pages 61—67 Download:  PDF (175  Kb, Info) Keywords: Generalized nets, Integrated circuit wafers References: Atanassov, K. Generalized Nets, World Scientific. Singapore, New Jersey, London, 1991. Atanassov, K., Introduction in the theory of the generalized nets, Pontika-Print, Bourgas, 1992. Haykin, S, Neural network and comprehensive foundation, Prentice Hall, New Jersey, 1999. Howard Demuth, Mark Beale, Neural network design, Prentice hall, New Jersey, 1995. Atanasov Kr., E. Sotirova, On global Operator G21 defined over Generalized Nets, Cybernetics and information technologies, Volume 4 No 2, Bulgarian Academy of Science, Sofia, 2004. Citations: Issue:Generalized net model of the intuitionistic fuzzy feed forward neural network ‎ (← links) Issue:Modeling the work of learning vector quantization neural networks ‎ (← links) Issue:Modelling the backpropagation algorithm of the Elman neural network by a generalized net ‎ (← links) The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.