Title :
Machine learning techniques in optical communication
Author :
D. Zibar;M. Piels;R. Jones;C. G. Schaeffer
Author_Institution :
DTU Fotonik, Technical University of Denmark, Build. 343, DK-2800, Denmark
Abstract :
Techniques from the machine learning community are reviewed and employed for laser characterization, signal detection in the presence of nonlinear phase noise, and nonlinearity mitigation. Bayesian filtering and expectation maximization are employed within nonlinear state-space framework for parameter tracking.
Keywords :
"Phase noise","Nonlinear optics","Optical noise","Optical polarization","Bayes methods","Optical signal processing","Optical variables measurement"
Conference_Titel :
Optical Communication (ECOC), 2015 European Conference on
DOI :
10.1109/ECOC.2015.7341896