Issue:Modeling the work of learning vector quantization neural networks

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http://ifigenia.org/wiki/issue:iwgn-2006-39-44

Title of paper: Modeling the work of learning vector quantization neural networks Author(s): Maciej Krawczak Systems Research Institute - Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland krawczak@ibspan.waw.pl Sotir Sotirov "Prof. Asen Zlatarov" University, Bourgas-8000, Bulgaria ssotirov@btu.bg Vassilis Kodogiannis Centre for Systems Analysis, School of Computer Science, University of Westminster, London HA1 3TP, United Kingdom kodogiv@wmin.ac.uk Presented at: 7th International Workshop on Generalized Nets, Sofia, 14-15 July 2006 Published in: Conference proceedings, pages 39—44 Download:  PDF (155  Kb, File info) Abstract: In this paper we introduce e GN-model of the work of Learning Vector Quantization neural networks. The model can be used for the optimization and following the network’s behavior in future. Keywords: Neural network, Generalized nets, LVQ References: Atanassov, K., Generalized nets, World Scientific, Singapore, New Jersey, London 1991 Hagan, M. T., H. B. Demuth, and M. H. Beale, Neural Network Design, Boston, MA: PWS Publishing, 1996. Haykin, S. (1994), Neural Networks: A Comprehensive Foundation, NY: Macmillan. Kohonen, T., Self-Organizing and Associative memory: 2nd Ed. Berlin, Springer-Verlag, 1987 Krawczak M., Generalized Net Models of Systems, Bulletin of Polish Academy of Science, 2003 Krawczak M., Aladjov, H., Generalized Net Model of adjoint Neural Network, Advanced Studies in Contemporary Mathematics, 2003 Maeda Y., Toshiki Tada, FPGA Implementation of a Pulse Density Neural Network With Training Ability Using Simultaneous Perturbation, IEEE Transactions on Neural Networks, Vol. 14, No. 3, May 2003 Sotirov S. Modeling the algorithm backpropagation for learning of neural networks with generalized nets. Part 1, Proceedings of the Fourth International Workshop on Generalized Nets, Sofia, 23 September 2003, 61-67 Sotirov S. Modeling the algorithm backpropagation for learning of neural networks with generalized nets. Part 2, Issues in Intuitionistic Fuzzy Sets and Generalized Nets, Warszawa, 2003, 65-70 Sotirov S., Modeling the accelerating Back Propagation algorithm with generalized nets, Advanced studies in contemporary Mathematics, 2006 Sotirov S., Modeling the work of self organizing neural network with generalized nets, Issues in Intuitionistic Fuzzy Sets and Generalized nets, Warszawa, 2003, 57-64 Citations: Issue:Generalized net model of hierarchical neural networks ‎ (← 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.