Optical frequency comb noise characterization using machine learning

Giovanni Brajato*, Lars Lundberg, Victor Torres-Company, Darko Zibar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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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.
Original languageEnglish
Title of host publicationProceedings of 45th European Conference on Optical Communication
Number of pages4
PublisherInstitution of Engineering and Technology
Publication date2019
ISBN (Print)9781839531859
Publication statusPublished - 2019
Event45th European Conference on Optical Communication - Royal Dublin Showground, Dublin, Ireland
Duration: 22 Sep 201926 Sep 2019
Conference number: 45
http://www.ecoc2019.org

Conference

Conference45th European Conference on Optical Communication
Number45
LocationRoyal Dublin Showground
CountryIreland
CityDublin
Period22/09/201926/09/2019
Internet address

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