Self-organizing map formation with a selectively refractory neighborhood

Neural Processing Letters

Volumn 39, Issue 1, 2014, Pages 1-24

  Neme, Antonio ^a,b   Miramontes, Pedro ^c  

^a UNIVERSIDAD AUTÓNOMA DE LA CIUDAD DE MÉXICO   (Mexico)

^b UNIVERSITY OF HELSINKI   (Finland)

^c UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

Author keywords

Asymmetric neighborhood; Map formation; Self organizing maps

Indexed keywords

ASYMMETRIC NEIGHBORHOOD; BEST MATCHING UNITS; ERROR MEASURES; FINAL STATE; HIGH-DIMENSIONAL; MAP FORMATION; SELF ORGANIZATIONS; SOM ALGORITHMS;

REFRACTORY MATERIALS; SELF ORGANIZING MAPS;

CONFORMAL MAPPING;

EID: 84893711402     PISSN: 13704621     EISSN: 1573773X     Source Type: Journal    
DOI: 10.1007/s11063-013-9287-8     Document Type: Article

References (35)

1. Cottrell M, Fort JC, Pagés G (1998) Theoretical aspects of the SOM algorithm. Neurocomputing 21:119-138
2. Kohonen T (2000) Self-Organizing maps, 3rd edn. Springer, New York
3. Ritter H (1999) Self-organizing maps on non-euclidean spaces. In: Oja E, Kaski S (eds) Kohonen maps. Elsevier, Amsterdam, pp 97-108
4. Yin Hujun (2008) The self-organizing maps: background, theories, extensions and applications. Computational intelligence: a compendium 2008:715-762
5. Van Hulle M (1997) Topology-preserving map formation achieved with a purely local unsupervised competitive learning rule. Neural Netw 10(3):431-446
6. Flanagan J (1999) Sufficient conditions for self-organization in the SOM with a decreasing neighborhood function of any width. In: Conference of artificial neural networks. Conference Pub 470
7. Erwin E, Obermayer K, Schulten K (1992) Self-organizing maps: ordering. convergence properties and energy functions. Biol Cyb 67:47-55
8. Berglund E, Sitte J (2006) The parameterless self-organizing map algorithm. IEEE Trans Neural Netw 17(2):305-316
9. Erwin E, Obermayer K, Schulten K (1992b) self-organizing maps: stationary states, metastability and convergence rate. Biol Cyb 67:35-45
10. Bamford SA, Af Murray (2010) Synaptic rewiring for topographic map formation and receptive field development. Neural Netw 23:517-527
11. Maia JEB, Barreto GA, Coelho ALV (2011) Visual object tracking by an evolutionary self-organizing neural network. J Intell Fuzzy Syst 22(2-3):69-81
12. Willshaw D, Malsburg C (1976) How patterned neural connections can be set up by self-organization. Proc R Soc Lond 194:431-445
13. Buzsaki G (2010) Neural syntax: cell assemblies, synapsembles, and readers. Neuron 68(3):362-85.
14. Miikkulainen R, Bednar J, Choe, S (2005) Computational maps in the visual cortex. Springer, New York
15. Forciniti L, Schmidt CE, Zaman H (2009) Computational model provides insight into the distinct responses of neurons to chemical and topographical cues. Ann Biomed Eng 37(2):363-374
16. Tamarit F, Stariolo D, Cannas A, Serras P (1996) Effects of refractory periods in the dynamics of a diluted neural network. Phys Rev E 53:51465152
17. Neme A, Hernández S, Neme O (2011) An electoral preferences model based on self-organizing maps. J Comput Sci 2(4):345-352
18. Neme A, Hernández S, Neme O, Hernández (2009) Self-organizing maps with non-cooperative strategies. In: Advances in self-organizing maps. Springer, New York, pp 200-208
19. Trappenberg T, Hartono P, Rasmusson D (2009) Top-down control of learning in biological self-organizing maps. WSOM 2009:316-324
20. Aoki T, Aoyagi T (2007) Self-organizing maps with asymmetric neighborhood function. Neural Comput 19(9):2515-2535
21. Neme A, Miramontes P (2006) A parameter in the SOM learning rule that incorporates activation frequency. ICANN 1:455-463
22. Lee J, Verleysen M (2002) Self-organizing maps with recursive neighborhood adaption. Neural Netw 15:993-1003
23. Bauer H, Pawelzik K (1992) Quantifying the neighborhood preservation in self-organizing feature maps. IEEE Trans Neural Netw 3(4):570-579
24. Bauer H, Herrmann M, Villmann T (1999) Neural maps and topographic vector quantization. Neural Netw 12(4-5):659-676
25. Kiviluoto K (1996) Topology preservation in self-organizing maps. In: Proceedings of ICNN96, IEEE international conference on neural networks
26. Venna J, Kaski S (2001) Neighborhood preservation in nonlinear projection methods: an experimental study. In: Dorffner G, Bischof H, Hornik K (eds) ICANN 2001, vol 2130. Springer, New York, pp 485-491
27. Mayer R, Neumayer R, Baum D, Rauber A (2009) Analytic comparison of self-organising maps. In: WSOM 2009. LNCS, vol 5629, pp 182-190
28. Cover T Thomas J (2006) Elements of information theory. Wiley, New York
29. Cellucci CJ, Albano AM, Rapp PE (2005) Statistical validation of mutual information calculations: comparison of alternative numerical algorithms. Phys Rev E 71:066208
30. Neme A, Nido A, Mireles V, Miramontes P (2008) The self-organized chaos game representation for genomic signatures analysis. Learn Nonlinear Models 6(2):111-120
31. Almeida J, Carrico J, Maretzek A, Noble P, Fletcher M (2001) Analysis of genomic sequences by chaos game representatio. Bioinformatics 17(5):429-437
32. Jeffrey J (1998) Chaos game representation of sequences in Chaos and Fractals: a computer graphical journey. Pickover
33. Carreón G, Hernández E, Miramontes P (2005) DNA circular game of chaos. In: Uribe F, Garcia-Colín L (eds) Statistical physics and beyond, American Institute of Physics
34. Aoki T, Ota K, Kurata K (2009) Ordering process of self-organizing maps improved by asymmetric neighborhood function. Cogn Neurodyn 3:9-15. doi: 10.1007/s11571-008-9060-2
35. Murakochi K, Sato Y (2007) Reducing topological defects in self-organizing maps using multiple scale neighborhood functions. Biosystems 90-1:101-104