Hamming neural network in discrete form

Abstract

Hamming artificial neural network is used to solve problems of classification of binary input vectors. Its work is based on procedures aimed at choosing, as a solution to the classification problem, one of the reference images closest to the noisy input image supplied to the network input and assigning this image to the corresponding class. At the same time, difficulties were identified in implementing calculations of the Hamming neural network paradigm. One of the ways to simplify computations in the considered neural network paradigm is to transition to integer computations since integer multiplication is computed several times faster than real data type. To simplify the computation model, a Hamming neural network in discrete form was proposed in this paper. A discrete model of the Hamming neural network is proposed, making it possible to simplify the implementation of computations significantly. These results can be applied to solve various problems, including computer vision applications.