Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques

Khouloud Abdelli; Khouloud Abdelli; Danish Rafique; Helmut Grießer; Stephan Pachnicke

doi:10.1364/OFC.2020.Th2A.3

Optical Fiber Communication Conference (OFC) 2020
OSA Technical Digest (Optica Publishing Group, 2020),
paper Th2A.3
•https://doi.org/10.1364/OFC.2020.Th2A.3

Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques

Khouloud Abdelli, Danish Rafique, Helmut Grießer, and Stephan Pachnicke

Optical Fiber Communication Conference 2020

San Diego, California United States
8–12 March 2020
ISBN: 978-1-943580-71-2

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Poster Session II (Th2A)

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K. Abdelli, D. Rafique, H. Grießer, and S. Pachnicke, "Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques," in Optical Fiber Communication Conference (OFC) 2020, OSA Technical Digest (Optica Publishing Group, 2020), paper Th2A.3.

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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.

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