Definition of an energy function for the random neural to solve optimization problems

Abstract

In this paper, we propose a general energy function for a new neural model, the random neural model of Gelenbe. This model proposes a scheme of interaction between the neurons and not a dynamic equation of the system. We then apply this general energy function on different optimization problems: the graph partitionning problem and the minimum node coveting problem.