Copyright © 2010 Mauro Tucci and Marco Raugi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

1. T. Kohonen, “The self-organizing map,” Neurocomputing, vol. 21, no. 1–3, pp. 1–6, 1998.
2. T. Kohonen, Self-Organization and Associative Memory, Springer, Berlin, Germany, 3rd edition, 1989.
3. T. Kohonen, Self-Organizing Maps, Springer, Berlin, Germany, 3rd edition, 2001.
4. S. Kaski, T. Honkela, K. Lagus, and T. Kohonen, “WEBSOM—self-organizing maps of document collections,” Neurocomputing, vol. 21, no. 1–3, pp. 101–117, 1998. View at Publisher · View at Google Scholar · View at Scopus
5. T. Kohonen and P. Somervuo, “Self-organizing maps of symbol strings,” Neurocomputing, vol. 21, no. 1–3, pp. 19–30, 1998. View at Publisher · View at Google Scholar · View at Scopus
6. T. Kohonen, E. Oja, O. Simula, A. Visa, and J. Kangas, “Engineering applications of the self-organizing map,” Proceedings of the IEEE, vol. 84, no. 10, pp. 1358–1383, 1996. View at Scopus
7. E. Erwin, K. Obermayer, and K. Schulten, “Self-organizing maps: ordering, convergence properties and energy functions,” Biological Cybernetics, vol. 67, no. 1, pp. 47–55, 1992. View at Publisher · View at Google Scholar · View at Scopus
8. E. Meŕenyi, A. Jain, and T. Villmann, “Explicit magnification control of self-organizing maps for "Forbidden" data,” IEEE Transactions on Neural Networks, vol. 18, no. 3, pp. 786–797, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
9. Y. Zheng and J. F. Greenleaf, “The effect of concave and convex weight adjustments on self-organizing maps,” IEEE Transactions on Neural Networks, vol. 7, no. 1, pp. 87–96, 1996. View at Scopus
10. J. Cho, A. R. C. Paiva, S. P. Kim, J. C. Sanchez, and J. C. Príncipe, “Self-organizing maps with dynamic learning for signal reconstruction,” Neural Networks, vol. 20, no. 2, pp. 274–284, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
11. Y. M. Cheung and L. T. Law, “Rival-model penalized self-organizing map,” IEEE Transactions on Neural Networks, vol. 18, no. 1, pp. 289–295, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
12. S. Cho and J. Seok, “Self-organizing map with time-invariant learning rate and its exponential stability analysis,” Neurocomputing, vol. 19, no. 1–3, pp. 1–11, 1998. View at Publisher · View at Google Scholar · View at Scopus
13. D. Theofilou, V. Steuber, and E. De Schutter, “Novelty detection in a Kohonen-like network with a long-term depression learning rule,” Neurocomputing, vol. 52-54, pp. 411–417, 2003. View at Scopus
14. E. Berglund and J. Sitte, “The parameterless self-organizing map algorithm,” IEEE Transactions on Neural Networks, vol. 17, no. 2, pp. 305–316, 2006. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
15. H. Shah-Hosseini and R. Safabakhsh, “TASOM: a new time adaptive self-organizing map,” IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 33, no. 2, pp. 271–282, 2003. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
16. K. Haese, “Self-organizing feature maps with self-adjusting learning parameters,” IEEE Transactions on Neural Networks, vol. 9, no. 6, pp. 1270–1278, 1998. View at Scopus
17. A. Antoniou, Digital Filters: Analysis, Design, and Applications, McGraw-Hill, New York, NY, USA, 1993.
18. T. M. Martinetz, S. G. Berkovich, and K. J. Schulten, “'Neural-gas' network for vector quantization and its application to time-series prediction,” IEEE Transactions on Neural Networks, vol. 4, no. 4, pp. 558–569, 1993. View at Publisher · View at Google Scholar · View at PubMed
19. A. Ultsch, “U*-matrix: a tool to visualize clusters in high dimensional data,” Tech. Rep., University of Marburg, 2000.
20. D. Lepetz, M. Némoz-Gaillard, and M. Aupetit, “Concerning the differentiability of the energy function in vector quantization algorithms,” Neural Networks, vol. 20, no. 5, pp. 621–630, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
21. J. Rynkiewicz, “Self-organizing map algorithm and distortion measure,” Neural Networks, vol. 19, no. 6-7, pp. 830–837, 2006. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
22. R. A. Fisher, “The use of multiple measurements in taxonomic problems,” Annals of Eugenics, vol. 7, pp. 179–188, 1936.