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
    PublisherInstitution of Engineering and Technology
    Publication date2019
    Pages572-575
    ISBN (Print)9781839531859
    DOIs
    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
    Country/TerritoryIreland
    CityDublin
    Period22/09/201926/09/2019
    Internet address

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