The statistical mechanics of image recovery and pattern recognition

Abstract

Many kinds of problems in physics and engineering can be cast as optimization problems in which a solution must be picked out of a very large and ‘‘complicated’’ solution candidate space. The simulated annealing algorithm, which derives from statistical mechanical theory, and Bayes’ theorem are introduced and it is shown how they can be combined to solve such problems. As an example, the problem of image recovery from noisy data is considered.