Simulation of associative memory in living beings - Generalization of the Hebb principle

This paper gives a model of neural networks whose purpose is the simulation of memory processing as it is assumed to be that of the biologic neural systems. The system learns chains of symbols. If after we give the first symbol of the chain, according with the principle of HEBB which if that of idea's associations, it repeats the following and that up to the end of the chain. If we give to different chains, it can after chose that if the nearest of the characters injected. As biologic systems, it is able to recognise the signal injected with different cadences or chose the chain which was the best learned. As biologics systems, it occurs that it doubts between two solutions or speaks indistinctly.