title: A principal components analysis self-organizing map.
abstract: We propose a new self-organizing neural model that performs principal components analysis. It is also related to the adaptive subspace self-organizing map (ASSOM) network, but its training equations are simpler. Experimental results are reported, which show that the new model has better performance than the ASSOM network.
authors.affiliation: Department of Computer Science, Universidad de Málaga, Campus de Teatinos, s/n. 29071 Málaga, Spain. ezeqlr@lcc.uma.es
authors.forename: Ezequiel
authors.initials: E
authors.lastname: López-Rubio
authors.forename: José
authors.initials: J
authors.lastname: Muñoz-Pérez
authors.forename: José Antonio
authors.initials: JA
authors.lastname: Gómez-Ruiz
mesh_terms: D016571:Neural Networks, Computer; D025341:Principal Component Analysis / Q000379:methods*