Competitive learning for self organizing maps used in classification of partial discharges
Rubén Jaramillo Vacio, Carlos Alberto Ochoa Ortiz Zezzatti, Julio César Ponce Gallegos · Programación matemática y software · 2013
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.