Abstract
A model of a fully interconnected neural network composed of neurons having a refractory period and integrating the afferent signals is presented. A theoretical analysis of its dynamics is carried out, considering the general case with periodic input and output sequences from which a teaching algorithm for storing periodic sequences in the network is derived. Finally, the performances of the network are illustrated through a selected example and its potentialities, as well as its possible applications, are discussed.
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