Memory topology of neural nets

Abstract

Aiming at a topology of memory-growth, a computer-simulated mechanism is developed here, based on the probabilistic neural model previously developed by Anninos, Csermeley & Harth. The essential topology of this mechanism reflects the generally accepted idea that memory growth is achieved by means of association processes, i.e. through the cross-referencing of new inputs with already acquired information. In terms of computer-simulation such mechanism is developed by following the formalism of Set Theory. So the memory units, i.e. the neural netlets are equated to subsets of a set which represents a larger memory-system. Consistently with this formalism, association is a necessary, although non-sufficient condition for the growth of memory and the Boolean overlap of two subsets, i.e. of two netlets, is identified with the cross-reference mechanism which we assume to be the basis of memory growth.