A general assembly as implementation of a Hebbian rule in a Boolean neural network

Usually the Hebbian learning spontaneously seems to produce associative memory behavior in the network where they are applied. The unsupervised learning performed by the Hebbian rule, automatically 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.