Competitive learning for self organizing maps used in classification of partial discharges
DOI:
https://doi.org/10.30973/progmat/2013.5.2/2Palabras clave:
aprendizaje competitivo, mapas autoorganizados, descargas parciales, métricas de calidad, diagnósticoResumen
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.
Citas
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Derechos de autor 2013 Ruben Jaramillo-Vacio, Carlos Alberto Ochoa Ortiz Zezzatti , Julio César Ponce Gallegos

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