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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