Khouloud Abdelli, D. Rafique, H. Griesser, S. Pachnicke
{"title":"基于机器学习技术的1550 nm DFB激光器寿命预测","authors":"Khouloud Abdelli, D. Rafique, H. Griesser, S. Pachnicke","doi":"10.1364/OFC.2020.Th2A.3","DOIUrl":null,"url":null,"abstract":"A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 μm InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime projection using accelerated aging tests.","PeriodicalId":173355,"journal":{"name":"2020 Optical Fiber Communications Conference and Exhibition (OFC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Lifetime Prediction of 1550 nm DFB Laser using Machine Learning Techniques\",\"authors\":\"Khouloud Abdelli, D. Rafique, H. Griesser, S. Pachnicke\",\"doi\":\"10.1364/OFC.2020.Th2A.3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 μm InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime projection using accelerated aging tests.\",\"PeriodicalId\":173355,\"journal\":{\"name\":\"2020 Optical Fiber Communications Conference and Exhibition (OFC)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Optical Fiber Communications Conference and Exhibition (OFC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/OFC.2020.Th2A.3\",\"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 Optical Fiber Communications Conference and Exhibition (OFC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/OFC.2020.Th2A.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lifetime Prediction of 1550 nm DFB Laser using Machine Learning Techniques
A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 μm InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime projection using accelerated aging tests.
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