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Issue:Generalized net model of hierarchical neural networks

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Title of paper: Generalized net model of hierarchical neural networks
Author(s):
Krassimir Atanassov
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy Sciences, 1 “Prof. Yakimov” Blvd, Burgas–8010, Bulgaria
“Prof. Asen Zlatarov” University
krat@bas.bg
Sotir Sotirov
“Prof. Asen Zlatarov” University, 1 “Prof. Yakimov” Blvd, Burgas–8010, Bulgaria
ssotirov@btu.bg
Anthony Shannon
Faculty of Engineering & IT, University of Technology, Sydney, Sydney, NSW 2007, Australia
Anthony.Shannon@uts.edu.au
Presented at: 13th IWGN, London, 29 October 2012
Published in: Conference proceedings, pages 8—14
Download: Download-icon.png PDF (81  Kb, Info)
Abstract: We construct here a Generalized Net (GN) that represents the functioning and the results of the work of real processes and simultaneously – the processes of their control and optimization on the basis of different suitably chosen hierarchical neural networks solving concrete optimization procedures and using information generated in the GN.
Keywords: Control, Generalized net, Neural network, Optimization.
AMS Classification: 68Q85, 62M45.
References:
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