Adaptive fir neural model for centroid learning in self-organizing maps

IEEE Transactions on Neural Networks

Volumn 21, Issue 6, 2010, Pages 948-960

  Tucci, Mauro ^a   Raugi, Marco ^a  

^a UNIVERSITY OF PISA   (Italy)

Author keywords

Cluster structure visualization; Self organizing maps (SOMs); Sequential learning; Stochastic gradient descent methods

Indexed keywords

CLUSTER DENSITIES; CLUSTER STRUCTURE; CLUSTER STRUCTURE VISUALIZATION; DISTORTION MEASURES; FINITE-IMPULSE RESPONSE; FIR MODEL; MOVING AVERAGE FILTER; NEURAL MODELS; NEW MODEL; ORDERED SET; PROCESSING UNITS; SEQUENTIAL LEARNING; STOCHASTIC GRADIENT; TOPOLOGY PRESERVING MAPS; TRAINING METHODS;

CONFORMAL MAPPING; FIR FILTERS; IMPULSE RESPONSE; OPTIMIZATION; STOCHASTIC SYSTEMS; STRENGTH OF MATERIALS; VISUALIZATION;

SELF ORGANIZING MAPS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; COMPUTER SIMULATION; FEEDBACK SYSTEM; HUMAN; LEARNING; NERVE CELL; NONLINEAR SYSTEM; PHYSIOLOGY; STATISTICS;

ALGORITHMS; COMPUTER SIMULATION; FEEDBACK; HUMANS; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); NEURONS; NONLINEAR DYNAMICS; SERIAL LEARNING; STOCHASTIC PROCESSES;

EID: 77953085509     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2046180     Document Type: Article

References (31)

1. L. Aguayo and G. Barreto, "Detection of anomalies and novelties in time series with self-organizing networks," in Proc. 6th Int. Workshop Self-Organizing Maps, Sep. 2007, DOI: 10.2390/biecoll-wsom2007-125, ISBN: 978-3-00-022473-22477
2. A. Asuncion and D. J. Newman, UCI Machine Learning Repository, Schl. Inf. Comput. Sci., Univ. California, Irvine, CA [Online]. Available: http://www.ics.uci.edu/~mlearn/MLRepository.html
3. E. Berglund and J. Sitte, "The parameterless self-organizing map algorithm," IEEE Trans. Neural Netw., vol.17, no.2, pp. 305-316, Mar. 2006.
4. Y. M. Cheung and L. Law, "Rival-model penalized self-organizing map," IEEE Trans. Neural Netw., vol.18, no.1, pp. 289-295, Jan. 2007.
5. 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.
6. E. Erwin, K. Obermayer, and K. Schulten, "Self-organizing maps: Ordering, convergence properties and energy functions," Biol. Cybern., vol.67, no.1, pp. 47-55, 1992.
7. G. R. de Haan and O. Egecioglu, "Links between self-organizing maps and weighted vector quantization," in Proc. IEEE Int. Joint Conf. Neural Netw., Seattle, WA, Jul. 1991, pp. 887-892.
8. K. Haese, "Self-organizing feature maps with self-adjusting learning parameters," IEEE Trans. Neural Netw., vol.9, no.6, pp. 1270-1278, Nov. 1998.
9. S. Haykin, Adaptive Filter Theory, 4th ed. Englewood Cliffs, NJ: Prentice-Hall, 2002.
10. A. Hirose and T. Nagashima, "Predictive self-organizing map for vector quantization of migratory signals and its application to mobile communications," IEEE Trans. Neural Netw., vol.14, no.6, pp. 1532-1540, Nov. 2003.
11. M. M. V. Hulle, "Kernel-Based topographic map formation by local density modeling," Neural Comput., vol.14, no.7, pp. 1561-1573, 2002.
12. S. Kaski, T. Honkela, K. Lagus, and T. Kohonen, "WEBSOM7- Selforganizing maps of document collections," Neurocomputing, vol.21, no.1-3, pp. 101-117, 1998.
13. T. Kohonen, "The self-organizing map," Proc. IEEE, vol.78, no.9, pp. 1464-1480, Sep. 1990.
14. T. Kohonen, Self-Organizing Maps, 3rd ed. Berlin, Germany: Springer-Verlag, 2001.
15. T. Kohonen, E. Oja, O. Simula, A. Visa, and J. Kangas, "Engineering applications of the self-organizing map," Proc. IEEE, vol.84, no.10, pp. 1358-1384, Oct. 1996.
16. J. Lampinen and E. Oja, "Self-organizing for spatial and temporal AR models," in Proc. 6th Scandinavian Conf. Image Anal., Oulu, Finland, Jun. 1989, pp. 120-127.
17. J. A. Lee and M. Verleysen, "Self-organizing maps with recursive neighborhood adaptation," Neural Netw., vol.15, no.8-9, pp. 993-1003, 2002.
18. E. Merenyi, A. Jain, and T. Villmann, "Explicit magnification control of self-organizing maps for "forbidden" data," IEEE Trans. Neural Netw., vol.18, no.3, pp. 786-797, May 2007.
19. D. Park, "Centroid neural network for unsupervised competitive learning," IEEE Trans. Neural Netw., vol.11, no.2, pp. 520-528, Mar. 2000.
20. G. Polzbauer, M. Dittenbach, and A. Rauber, "Advanced visualization of self-organizing maps with vector fields," Neural Netw., vol.19, no.6-7, pp. 911-922, 2006.
21. J. Rynkiewicz, "Self-organizing map algorithm and distortion measure," Neural Netw., vol.19, pp. 830-837, Aug. 2006.
22. H. Shah-Hosseini and R. Safabakhsh, "TASOM: A new time adaptive self-organizing map," IEEE Trans. Syst. Man Cybern. B, Cybern., vol.33, no.2, pp. 271-282, Apr. 2003.
23. K. Tasdemir and E. Merenyi, "Exploiting data topology in visualization and clustering of self-organizing maps," IEEE Trans. Neural Netw., vol.20, no.4, pp. 549-562, Apr. 2009.
24. 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.
25. A. Ultsch, " U* -matrix: A tool to visualize clusters in high dimensional data," Dept. Math. Comput. Sci., Philipps-University Marburg, Marburg, Germany, Internal Rep., 2003.
26. A. Ultsch, "Maps for the visualization of high-dimensional data spaces," in Proc. 4th Int. Workshop Self-Organizing Maps, Kyushu, Japan, Sep. 2003, pp. 225-230.
27. A. Ultsch, "Pareto density estimation: Probability density estimation for knowledge discovery," in Proc. 27th Annu. Conf. Gesellschaft Für Klassifikation, Cottbus, Germany, Mar. 2003, pp. 91-100.
28. M. Varsta, J. Heikkonen, J. del, and R. Millan, "Context-learning with the self-organizing map," in Proc. 1st Int. Workshop Self-Organizing Maps, Helsinki, Finland, Jun. 1997, pp. 197-202.
29. G. G. Yen and W. Zheng, "Ranked centroid projection: A data visualization approach with self-organizing maps," IEEE Trans. Neural Netw., vol.19, no.2, pp. 245-259, Feb. 2008.
30. Z. Yi and J. F. Greenleaf, "The effect of concave and convex weight adjustments on self-organizing maps," IEEE Trans. Neural Netw., vol.7, no.1, pp. 87-96, Jan. 1996.
31. H. Yin and H. Ni, "Generalized self-organizing mixture autoregressive model," in Proc. 7th Int. Workshop Self-Organizing Maps, Jun. 2009, pp. 353-361.