• DocumentCode
    3701201
  • Title

    Machine learning techniques in optical communication

  • Author

    D. Zibar;M. Piels;R. Jones;C. G. Schaeffer

  • Author_Institution
    DTU Fotonik, Technical University of Denmark, Build. 343, DK-2800, Denmark
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Techniques from the machine learning community are reviewed and employed for laser characterization, signal detection in the presence of nonlinear phase noise, and nonlinearity mitigation. Bayesian filtering and expectation maximization are employed within nonlinear state-space framework for parameter tracking.
  • Keywords
    "Phase noise","Nonlinear optics","Optical noise","Optical polarization","Bayes methods","Optical signal processing","Optical variables measurement"
  • Publisher
    ieee
  • Conference_Titel
    Optical Communication (ECOC), 2015 European Conference on
  • Type

    conf

  • DOI
    10.1109/ECOC.2015.7341896
  • Filename
    7341896
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3701201