Abstract

This paper, taking as inspiration the ideas proposal for the TNGS (Theory of Neuronal Group Selection), presents a study of convergence capacity of two-level associative memories based on coupled Generalized-Brain-State-in-a-Box (GBSB) neural networks. In this model, the memory processes are described as being organized functionally in hierarchical levels, where the higher levels would coordinate sets of function of the lower levels. Simulations were carried out to illustrate the behaviour of the capacity of the system for a wide range of the system parameters considering linearly independent (LI) and orthogonal vectors. The results obtained show the relations amongst convergence, intensity and density of coupling.

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