LEARNING ALGORITHM FOR MEAN FIELD THEORY OF THE HIGHER-ORDER BOLTZMANN MACHINE
高阶Boltzmann机的平均场理论学习算法

Using mean field theory (MFT) of statistical mechanics and simulated annealing technique. the determinate equation of relaxation kinetics of higher-order Boltzmann Machine (BM) and its MFT learning algorithm are deduced in a way different from that in reference2], which is combined with the merits of general higher-order neural network and Boltzmann Machine. Both are easy to be implemented by VLSI. The learning algorithm saves a lot of CPU time. The computer simulation results for two-dimentional mirror symmetries and T-C problem show that the MFT learning algorithm of the third-order BM is correct and better than that of second-order BM.