Usually the Hebbian learning spontaneously seems to produce associative memory behaviour in the network where they are applied. The unsupervised learning performed by the Hebbian rule, automaticaly creates associations into the network as soon as the responses to the inputs are computed. The paradigm we are discussing here is different from the classical unsupervised learning paradigm, and it is a quite general solution for the implementation of a a Hebbian rule in a Boolean neural network. Our system may not be seen as an associative memory only, it is both a controller and a classifier
A General Assembly as implementation of a Hebbian rule in a Boolean Neural Network / F., Lauria; M., Milo; Prevete, Roberto; S., Visco. - STAMPA. - (1999), pp. 266-271. (Intervento presentato al convegno Neural nets, WIRN Vietri-99 tenutosi a Vietri sul Mare, Salerno, Italy nel 20-22 May 1999}).
A General Assembly as implementation of a Hebbian rule in a Boolean Neural Network
PREVETE, ROBERTO;
1999
Abstract
Usually the Hebbian learning spontaneously seems to produce associative memory behaviour in the network where they are applied. The unsupervised learning performed by the Hebbian rule, automaticaly creates associations into the network as soon as the responses to the inputs are computed. The paradigm we are discussing here is different from the classical unsupervised learning paradigm, and it is a quite general solution for the implementation of a a Hebbian rule in a Boolean neural network. Our system may not be seen as an associative memory only, it is both a controller and a classifierI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.