Pedro J. Freire, Daniel Abode, J. Prilepsky, S. Turitsyn
{"title":"Power and Modulation Format Transfer Learning for Neural Network Equalizers in Coherent Optical Transmission Systems","authors":"Pedro J. Freire, Daniel Abode, J. Prilepsky, S. Turitsyn","doi":"10.1364/sppcom.2021.spm5c.6","DOIUrl":null,"url":null,"abstract":"Transfer learning is proposed to adapt an NN-based nonlinear equalizer across different launch powers and modulation formats using a 450km TWC-fiber transmission. The result shows up to 92% reduction in epochs or 90% in the training dataset.","PeriodicalId":117290,"journal":{"name":"OSA Advanced Photonics Congress 2021","volume":"195 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"OSA Advanced Photonics Congress 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/sppcom.2021.spm5c.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Transfer learning is proposed to adapt an NN-based nonlinear equalizer across different launch powers and modulation formats using a 450km TWC-fiber transmission. The result shows up to 92% reduction in epochs or 90% in the training dataset.