Long-term memory neural network modeling memory-chaining functions of the brain wherein a pointer holds information about mutually related neurons and neurons are classified hierarchically by degree of activation

摘要

A STM network 11 for temporarily storing input pattern vectors is formed in Phases 1 and 2, and then layered LTM networks 2 to L are formed successively by assigning output vectors provided by the STM network 11 as input vectors. In phase 4, a LTM network 1 for intuitive outputs to which input pattern vectors are applied directly is formed by taking the parameters of comparatively highly activated centroids among centroids in the LTM networks 2 to L. In phase 5, the parameters of the comparatively highly activated centroids among the centroids in the LTM networks 2 to L are fed back as the parameters of the centroids in the STM network. In phase 3, the LTM networks 2 to L are reconstructed at a particular time or in a fixed period by giving the centroid vectors of the LTM networks 2 to L again as input pattern vectors to the STM network 11.