Formation of Similarity-Reflecting Binary Vectors with Random Binary Projections

Abstract

We propose a transformation of real input vectors to output binary vectors by projection using a binary random matrix with elements {0,1} and thresholding. We investigate the rate of convergence of the distribution of vector components before binarization to the Gaussian distribution as well as its relationship to the estimation error of the angle between the input vectors by the binarized output vectors. It is shown that for the choice of projection parameters that provide nearly-Gaussian distribution, the experimental and analytical errors are close.