The optimal value of self-connection

Abstract

The fact that reducing self-connections improves the performance of the autoassociative networks built by the pseudo-inverse learning rule is known already for quite a while, but has not been studied in detail yet. In particular, it is known that decreasing of self-connection increases the direct attraction radius of the network, and it is also known that it increases the number of spurious dynamic attractors. Thus, it has been concluded that the optimal value of the coefficient of self-connection reduction D lies somewhere in the range (0; 0.5). This paper gives an explicit answer to the question on what is the optimal value of the self-connection reduction. It shows how the indirect attraction radius increases with the decrease of D. The summary of the results pertaining to the phenomenon is presented.