MAN: mass attraction network

In this study, a binary associative memory, inspired from Newton's mass attraction theory is proposed and some related analysis is given. In the model, memory items are considered as masses in the interior or at the corners of a hypercube. In recall, "attraction forces" are computed and the memory item, whose "force" is the greatest, becomes the output pattern. Since the operation of the model is highly parallel, the network is extremely fast. Retrieving a memory item takes only two steps. The proposed model has been observed to be superior to Hamming net, Hopfield network and Harmony theory in various aspects.<<ETX>>