A stochastic network with rotor neurons

We define a new network structure to realize a continuous version of the Boltzmann machine (BM). Based on the mean field (MF) theory for continuous and multidimensional elements, named rotors (introduced by Gislen and Peterson), we derive the corresponding MF learning algorithm. Simulations demonstrate the learning capability of this network for continuous mappings.