Competitive learning for self organizing maps used in classification of partial discharges

In this paper different competitive learning algorithms for self-organizing maps (SOM) are experimentally examined. The characterization of the results obtained is presented in terms of quality of SOM. The competitive learning algorithms evaluated through SOM are winner-takes-all, frequency sensitiv...

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Veröffentlicht in:Programación Matemática y Software 2013-11, Vol.5 (2), p.5-12
Hauptverfasser: Jaramillo Vacio, Ruben, Ochoa Ortiz Zezzatti, Carlos Alberto, Ponce Gallegos, Julio César
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Sprache:eng
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Zusammenfassung:In this paper different competitive learning algorithms for self-organizing maps (SOM) are experimentally examined. The characterization of the results obtained is presented in terms of quality of SOM. The competitive learning algorithms evaluated through SOM are winner-takes-all, frequency sensitive competitive learning, and rival penalized competitive learning. Case study: their performance in the classification of partial discharges on power cables.
ISSN:2007-3283
2007-3283
DOI:10.30973/progmat/2013.5.2/2