Machine learning methods for optical communication systems

Faisal Nadeem Khan, Chao Lu, Pak Tao Lau

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

We review application of machine learning methods to tackle fiber linear/nonlinear impairments as well as to estimate crucial signal parameters in optical networks. Recent works involving hierarchical learning approaches are also discussed.
Original languageEnglish
Title of host publicationAdvanced Photonics, SPPCom 2017
PublisherOSA - The Optical Society
VolumePart F59-SPPCom 2017
ISBN (Electronic)9781557528209
DOIs
Publication statusPublished - 1 Jan 2017
EventAdvanced Photonics, SPPCom 2017 - New Orleans, United States
Duration: 24 Jul 201727 Jul 2017

Conference

ConferenceAdvanced Photonics, SPPCom 2017
Country/TerritoryUnited States
CityNew Orleans
Period24/07/1727/07/17

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint

Dive into the research topics of 'Machine learning methods for optical communication systems'. Together they form a unique fingerprint.

Cite this