Retrieval characteristics of multiple site states networks with self-interaction

Abstract

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-interaction terms in an N = 401 network. They show that self-interaction enhances the storage capacity of a network, decreases the average error in retrieved patterns, and makes the search of patterns faster. In addition, a self-interacting network does not show a complete loss of memory at any stage. Instead, its memory degrades slowly so that retrieved patterns become progressively more and more erroneous. The relative weight of self-interaction is varied to determine its optimum amount in 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.