Abstract
This paper aims to propose an extension of SOMs called an “SOM of SOMs,” or SOM2, in which the mapped objects are self-organizing maps themselves. In SOM2, each nodal unit of the conventional SOM is replaced by a function module of SOM. Therefore, SOM2 can be regarded as a variation of a modular network SOM (mnSOM). Since each child SOM module in SOM2 is trained to represent a manifold, the parent SOM in SOM2 generates a self-organizing map representing the distribution of the group of manifolds modeled by the child SOMs. This extension of SOM is easily generalized in the case of SOMn, such that “SOM2 as SOM of SOM2s.” In this paper, the algorithm of SOM2 is introduced, and some simulation results are reported.
This work was supported by a COE program (center #J19) granted by MEXT of Japan.
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References
Kohonen, T.: Self-Organizing Maps, 3rd edn. Springer, Heidelberg (2001)
Tokunaga, K., Furukawa, T., Yasui, S.: Modular network SOM: Extension of SOM to the realm of function space. In: Proc. of WSOM 2003, pp. 173–178 (2003)
Furukawa, T., Tokunaga, K., Kaneko, S., Kimotsuki, K., Yasui, S.: Generalized self-organizing maps (mnSOM) for dealing with dynamical systems. In: Proc. of NOLTA 2004, pp. 231–234 (2004)
Kohonen, T.: Generalization of the Self-organizing map. In: Proc. of IJCNN 1993, pp. 457–462 (1993)
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Furukawa, T. (2005). SOM of SOMs: Self-organizing Map Which Maps a Group of Self-organizing Maps. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_61
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DOI: https://doi.org/10.1007/11550822_61
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