In this paper the drawbacks of classical unsupervised learning laws are discussed and the paradigms of an alternative clustering algorithm are carried out. Then a new model of neuron element able to search the centroid of clusters without competition with other neurons, as in an unsupervised competitive learning law, is singled out
Centroid estimation by means of uncompetitive unsupervised neural element / Acciani, G.; Chiarantoni, E.; Vacca, F.. - STAMPA. - (1993), pp. 426-429. (Intervento presentato al convegno 36th Midwest Symposium on Circuit and Systems tenutosi a Detroit, MI nel August 16-18, 1993) [10.1109/MWSCAS.1993.342997].
Centroid estimation by means of uncompetitive unsupervised neural element
G. Acciani;E. Chiarantoni;F. Vacca
1993-01-01
Abstract
In this paper the drawbacks of classical unsupervised learning laws are discussed and the paradigms of an alternative clustering algorithm are carried out. Then a new model of neuron element able to search the centroid of clusters without competition with other neurons, as in an unsupervised competitive learning law, is singled outFile in questo prodotto:
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