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

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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.

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Jose, A. (1998). Definition of an energy function for the random neural to solve optimization problems. Neural Networks, 11(4), 731–737. https://doi.org/10.1016/S0893-6080(98)00020-3

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