{"title":"SOA光通信系统中的机器学习","authors":"F. Matera","doi":"10.1109/ICOP49690.2020.9300311","DOIUrl":null,"url":null,"abstract":"The performance of cascaded optical communication systems with in-line semiconductor optical amplifiers is evaluated by means of machine learning approaches based both on a regression model and an artificial neural network.","PeriodicalId":131383,"journal":{"name":"2020 Italian Conference on Optics and Photonics (ICOP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine Learning in SOA Optical Communication Systems\",\"authors\":\"F. Matera\",\"doi\":\"10.1109/ICOP49690.2020.9300311\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performance of cascaded optical communication systems with in-line semiconductor optical amplifiers is evaluated by means of machine learning approaches based both on a regression model and an artificial neural network.\",\"PeriodicalId\":131383,\"journal\":{\"name\":\"2020 Italian Conference on Optics and Photonics (ICOP)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Italian Conference on Optics and Photonics (ICOP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOP49690.2020.9300311\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Italian Conference on Optics and Photonics (ICOP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOP49690.2020.9300311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine Learning in SOA Optical Communication Systems
The performance of cascaded optical communication systems with in-line semiconductor optical amplifiers is evaluated by means of machine learning approaches based both on a regression model and an artificial neural network.