Experimental Validation of Deep Learning-based Models for Optical Time Domain Analysis

Abstract

Optical constellations generated by Deep Learning models trained with datasets generated through simulation are compared to experimentally collected ones. The obtained high accuracy enables its application for optical time domain analysis in complex network scenarios.