Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106961
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dc.contributorPhotonics Research Centreen_US
dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.creatorKhan, FNen_US
dc.creatorLu, Cen_US
dc.creatorLau, APTen_US
dc.date.accessioned2024-06-07T00:59:09Z-
dc.date.available2024-06-07T00:59:09Z-
dc.identifier.isbn978-1-943580-38-5en_US
dc.identifier.urihttp://hdl.handle.net/10397/106961-
dc.descriptionOptical Fiber Communication Conference 2018, San Diego, California United States, 11-15 March 2018en_US
dc.language.isoenen_US
dc.publisherOptica Publishing Groupen_US
dc.rights© 2018 The Author(s)en_US
dc.rightsThe following publication F. N. Khan, C. Lu, and A. P. T. Lau, "Optical Performance Monitoring in Fiber-Optic Networks Enabled by Machine Learning Techniques," in Optical Fiber Communication Conference, OSA Technical Digest (online) (Optica Publishing Group, 2018), paper M2F.3 is available at https://doi.org/10.1364/OFC.2018.M2F.3.en_US
dc.titleOptical performance monitoring in fiber-optic networks enabled by machine learning techniquesen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1364/OFC.2018.M2F.3en_US
dcterms.abstractWe review applications of machine learning (ML) in various aspects of optical communications including optical performance monitoring, fiber nonlinearity compensation, and software-defined networking. The future role of ML in optical communications is also discussed.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationOptical Fiber Communication Conference, OSA Technical Digest (online) (Optica Publishing Group, 2018), paper M2F.3en_US
dcterms.issued2018-
dc.identifier.scopus2-s2.0-85047170706-
dc.relation.conferenceOptical Fiber Communication Conference [OFC]en_US
dc.identifier.artnM2F.3en_US
dc.description.validate202405 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberEIE-0598-
dc.description.fundingSourceRGCen_US
dc.description.fundingTextHong Kong Government General Research Funden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS9615340-
dc.description.oaCategoryVoR alloweden_US
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