Conference paper
Optical frequency comb noise characterization using machine learning
In
Proceedings of 45th European Conference on Optical Communication
—
2019, pp. 572-575
From
Machine Learning in Photonic Systems, Department of Photonics Engineering, Technical University of Denmark1
Department of Photonics Engineering, Technical University of Denmark2
Ultra-fast Optical Communication, Department of Photonics Engineering, Technical University of Denmark3
Chalmers University of Technology4
Abstract
A novel tool, based on Bayesian filtering framework and expectation maximization algorithm, is numerically and experimentally demonstrated for accurate frequency comb noise characterization. The tool is statistically optimum in a mean-square-error-sense, works at wide range of SNRs and offers more accurate noise estimation compared to conventional methods.
| Language: | English |
|---|---|
| Publisher: | Institution of Engineering and Technology |
| Year: | 2019 |
| Pages: | 572-575 |
| Proceedings: | 45th European Conference on Optical Communication |
| ISBN: | 1839531851 and 9781839531859 |
| Types: | Conference paper |
| DOI: | 10.1049/cp.2019.0889 |
| ORCIDs: | Zibar, Darko |
