In this paper, we propose a new method called collective activations to realize self-organizing maps. We suppose that all neurons collectively respond to input stimuli, and this collectiveness is represented by the sum of all neurons' activations. Learning consists of imitating these collective activations as much as possible. We applied the method to artificial data and a broadband survey problem. In all these problems, we could obtain self-organizing maps similar or, in some cases, superior to those obtained by conventional SOM. Thus, the present study is considered to be the first step toward more realistic self-organizing maps. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Kamimura, R. (2009). Collective activations to generate self-organizing maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5507 LNCS, pp. 943–950). https://doi.org/10.1007/978-3-642-03040-6_115
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