Machine learning concepts in coherent optical communication systems

Darko Zibar, Christian G. Schäffer

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

    Abstract

    Powerful statistical signal processing methods, used by the machine learning community, are addressed and linked to current problems in coherent optical communication. Bayesian filtering methods are presented and applied for nonlinear dynamic state tracking. © 2014 OSA.
    Original languageEnglish
    Title of host publicationProceedings of Signal Processing in Photonic Communications
    PublisherOptical Society of America (OSA)
    Publication date2014
    ISBN (Print)9781557527370
    Publication statusPublished - 2014
    EventSignal Processing in Photonic Communications - Hilton San Diego Resort & Spa, San Diego, United States
    Duration: 13 Jul 201416 Jul 2014

    Conference

    ConferenceSignal Processing in Photonic Communications
    LocationHilton San Diego Resort & Spa
    Country/TerritoryUnited States
    CitySan Diego
    Period13/07/201416/07/2014

    Keywords

    • Instrumentation
    • Atomic and Molecular Physics, and Optics
    • Artificial intelligence
    • Learning systems
    • Optical communication
    • Bayesian filtering
    • Coherent optical communication systems
    • Coherent optical communications
    • Current problems
    • Dynamic state tracking
    • Machine learning communities
    • Statistical signal processing
    • Signal processing

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