Notions of intuition and attention modeled by a hierarchically arranged generalized regression neural network

In this paper, two psychological functions, intuition and attention, are modeled by a newly proposed hierarchically arranged generalized regression neural network (HA-GRNN). The main contribution of the paper is two-fold: to provide an engineering basis for a macroscopic representation of psychology-oriented functions by means of artificial neural networks; to propose a concrete model for the two functions, intuition and attention, in terms of the associated interactive and evolutionary processes within an HA-GRNN. In the simulation study, the effectiveness of an HA-GRNN is justified within the context of pattern classification tasks.

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