Stochastic Recurrent Implementation of Local Recognition Algorithms

摘要

This paper is a continuation of [1]. A more complete description of the stochastic recurrent recognition algorithms suggested in [1] for estimating the part of the training information that is actually used for classifying a given object in local recognition is given. The pointwise convergence of these algorithms is proved.