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Advances in Artificial Neural Systems
Volume 2010 (2010), Article ID 142540, 10 pages
http://dx.doi.org/10.1155/2010/142540
Research Article

A Sequential Algorithm for Training the SOM Prototypes Based on Higher-Order Recursive Equations

Department of Electrical Systems and Automation, University of Pisa, via Diotisalvi 2, 56126 Pisa, Italy

Received 29 July 2010; Accepted 27 November 2010

Academic Editor: Songcan Chen

Copyright © 2010 Mauro Tucci and Marco Raugi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A novel training algorithm is proposed for the formation of Self-Organizing Maps (SOM). In the proposed model, the weights are updated incrementally by using a higher-order difference equation, which implements a low-pass digital filter. It is possible to improve selected features of the self-organization process with respect to the basic SOM by suitably designing the filter. Moreover, from this model, new visualization tools can be derived for cluster visualization and for monitoring the quality of the map.