Yprel nets and classification

In this paper we present a scheme of classification based on a particular processing element (“neuron”) called Yprel. The main characteristics of the approach are: (1) a Yprel classifier is a set of Yprel nets, each net being associated to a particular class; (2) the learning is supervised and conducted class by class; (3) the structure of the net is not a priori chosen, but is determined step by step during the learning process; and (4) partial re-learning and/or co-operation between nets can be added to improve the results. Preliminary results are given on a well-known classification task (recognition of typographic characters)