The Parameter-Less Self-Organizing Map algorithm

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dc.creatorBerglund, Erik
dc.creatorSitte, Joaquin
dc.date2007-05-02
dc.date2007-05-08
dc.date.accessioned2026-07-07T07:59:39Z
dc.date.available2026-07-07T07:59:39Z
dc.descriptionThe Parameter-Less Self-Organizing Map (PLSOM) is a new neural network algorithm based on the Self-Organizing Map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighbourhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.
dc.description29 pages, 27 figures. Based on publication in IEEE Trans. on Neural Networks
dc.identifierhttps://arxiv.org/abs/0705.0199
dc.identifierhttp://arxiv.org/abs/0705.0199
dc.identifierIEEE Transactions on Neural Networks, 2006 v.17, n.2, pp.305-316
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/128449
dc.subjectNeural and Evolutionary Computing
dc.subjectArtificial Intelligence
dc.subjectComputer Vision and Pattern Recognition
dc.titleThe Parameter-Less Self-Organizing Map algorithm
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