Community Research and Development Information Service - CORDIS

Multi SOMs

M-SOMs, Multi Self Organising (feature) Maps:
The Multi-SOM (M-SOM) approach is a newly variant of the Self Organizing Maps (SOM) which has the intriguing capability to allow a combination of supervised and self organised learning: Self-organised-supervised M-SOM learning.

Multi-SOMS consist of a set of partner SOMs, that are trained simultaneously and in
concurrence to each other. The different partner SOMs adapt to different classes.
M-SOMs are perfectly designed for Data-Mining and self organised data clustering.

The underlying properties of the data provided, is processed by the M-SOM and thereby classified. The size, shape and location of these classes is determined by the self organising features of the M-SOM. Each detected class is represented by a symbol of its own. Now, the M-SOM can be used to classify a given state of the system.

Reported by

Div. of Neural Computation, University of Bonn
Roemerstr. 164
53117 Bonn
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