Self-Organizing Map with Generating and Moving Neurons in Visible Space

Journal of Advanced Computational Intelligence and Intelligent Informatics

Volumn 11, Issue 6, 2007, Pages 626-632

  Tachibana, Kanta ^a   Furuhashi, Takeshi ^a  

^a NAGOYA UNIVERSITY   (Japan)

Author keywords

extension of mapping parameter; self organizing map; spherical visible space

Indexed keywords

CONFORMAL MAPPING; COSTS; ITERATIVE METHODS; LEARNING ALGORITHMS; NEURONS; SPHERES; TOPOLOGY; VISUALIZATION;

COMPUTATION COSTS; EXTENSION OF MAPPING PARAMETER; FEATURE SPACE; KOHONEN; MAPPING PARAMETERS; REFERENCE POINTS; SELF-ORGANIZING FEATURE MAP; SELF-ORGANIZING-MAPS; SPHERICAL VISIBLE SPACE; TOPOLOGY-PRESERVING MAPPINGS;

SELF ORGANIZING MAPS;

EID: 70349983985     PISSN: 13430130     EISSN: 18838014     Source Type: Journal    
DOI: 10.20965/jaciii.2007.p0626     Document Type: Article

References (24)

1. D. Alahakoon and S. K. Halgamuge, “Dynamic self-organizing maps with controlled growth for knowledge discovery,” IEEE Transaction on Neural Networks, 11(3), pp. 601-614, May 2000.
2. J. Blackmore and R. Miikkulainen, “Incremental grid growing: Encoding high-dimensional structure into a two-dimensional feature map,” In Proc. of the IEEE International Conference on Neural Networks (ICNN93), pp. 450-455, 1993.
3. J. Blackmore and R. Miikkulainen, “Visualizing high-dimensional structure with the incremental grid growing neural network,” In Proc. of the 12th International Conference on Machine Learning, 1995.
4. Q. Du, V. Faber, and M. Gunzburger, “Centroidal voronoi tessellations: Applications and algorithms,” Society for Industrial and Applied Mathematics Review, 41(4), pp. 637-676, October 1999.
5. B. Fritzke, “Let it grow – self-organizing feature maps with problem dependent cell structure,” In T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas (Eds.), Artificial Neural Networks, Vol.I, pp. 403-408, Amsterdam, Netherlands, North-Holland, 1991.
6. B. Fritzke, “Unsupervised clustering with growing cell structures,” In International Joint Conference on Neural Networks (IJCNN91), Vol.II, pp. 531-536, July 1991.
7. B. Fritzke, “Growing cell structures – a self-organizing network for unsupervised and supervised learning,” Neural Networks, 7, pp. 1441-1460, 1994.
8. B. German, “Glass identification database,” September 1987. available from ics.uci.edu at the directory/pub/machine-learning-databases/glass/.
9. S. Kaski and K. Lagus, “Comparing self-organizing maps,” Lecture Notes in Computer Science, 1112, pp. 809-814, 1996.
10. K. Kiviluoto, “Topology preservation in self-organizing maps,” In Proc. International Conference on Neural Networks (ICNN’96), Vol.1, pp. 294-299, 1996.
11. T. Kohonen, “Automatic formation of topological maps of patterns in a self-organizing system,” In Proc. 2nd Scand. Conf. on Image Analysis, pp. 214-220, 1981.
12. T. Kohonen, “Self-organized formation of topologically correct feature maps,” Biological Cybernetics, 43(1), pp. 59-69, January 1982.
13. T. Kohonen, “The speedy som,” Report a33, Helsinki University of Technology, Faculty of Information Technology, Laboratory of Computer and Information Science, 1996.
14. T. Kohonen, “Self-Organizing Maps,” Springer, 3rd edition, 2001.
15. T. Kohonen, J. Hynninen, J. Kangas, and J. Laaksonen, “Som pak: The self-organizing map program package,” Report a31, Helsinki University of Technology, Faculty of Information Technology, Laboratory of Computer and Information Science, Rakentajanaukio 2 C, SF-02150 Espoo, Finland, January 1996.
16. S. P. Lloyd, “Least squares quantization in pcm,” IEEE Transactions on Information Theory, IT-28(2), pp. 129-137, March 1982.
17. D. Nakatsuka and M. Oyabu, “Application of spherical som in clustering,” In Workshop on Self-Organizing Maps (WSOM03), pp. 203-207, 2003.
18. D. Polani, “Organization measures for self-organizing maps,” In T. Kohonen, (Ed.), Proc. Workshop on Self-Organizing Maps (WSOM97), pp. 280-285, 1997.
19. J. S. Rodrigues and L. B. Almeida, “Improving the learning speed in topological maps of patterns,” In Proc. of International Neural Networks Conference (INNC’90), pp. 813-816, 1990.
20. J. S. Rodrigues and L. B. Almeida, “Neural Networks: Advances and Applications,” chapter Improving the convergence in Kohonen topological maps, pp. 63-78. North-Holland, The Netherland, 1991.
21. A. Sangole and G. K. Knopf, “Visualization of randomly ordered numeric data sets using spherical self-organizing feature maps,” Computers & Graphics, 27, pp. 963-976, 2003.
22. K. Sugihara, “Robust gift wrapping for the three-dimensional convex hull,” J. Comput. Syst. Sci., 49(2), pp. 391-407, 1994.
23. K. Tachibana and T. Furuhashi, “A method to evaluate topological information for self-organizing maps,” In Proc. of Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems (SCIS&ISIS2006), pp. 2210-2213, 2006.
24. D. J. Watts, “A simple model of global cascades on random networks,” In Proc. of the National Academy of Sciences of the United States of America (PNAS), Vol.99, pp. 5766-5771, April 2002.