RETRIEVAL CHARACTERISTICS OF MULTIPLE-SITE STATES NETWORKS WITH SELF-INTERACTION

The Hopfield model of associative memory is modified by the inclusion of self-interaction and also by taking multiple site states networks. Computer simulations are presented to demonstrate the improvements in the retrieval characteristics as a result of the inclusion of self-int eraction terms in an N=401 network. They show that self-interaction en hances the storage capacity of a network, decreases the average error in retrieved patterns, and makes the search of patterns faster. In add ition, a self-interacting network does not show a complete loss of mem ory at any stage. Instead, its memory degrades slowly so that retrieve d patterns become progressively more and more erroneous. The relative weight of self-interaction is varied to determine its optimum amount i n an N = 100 network. This weight is then used to study the retrieval characteristics of a network of 3-states sites for N = 50. It is found that a self-interacting network 3-states sites is more efficient than the usual binary network.