Optical neural Al processing for binary pattern classification

Abstract

This paper discusses computer simulations and experimental designs for assessing the binary pattern classification capabilities of basic types of optical neural Al processor. After learning binary input patterns whose binary class is known, these processors classify patterns whose class is unknown. This classification task may be difficult if the relationship between pattern and class has no concise statement or algorithm, as in the case of random problems.1