A Machine Learning-Based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication
Author:
Affiliation:
1. ADVA Optical Networking SE, Munich/Martinsried, Germany
2. Kiel University (CAU), Chair of Communications, Kiel, Germany
Funder
CELTIC-NEXT
German Federal Ministry of Education and Research
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atomic and Molecular Physics, and Optics
Link
http://xplorestaging.ieee.org/ielx7/50/9826878/09756243.pdf?arnumber=9756243
Reference18 articles.
1. Federated Learning Approach for Lifetime Prediction of Semiconductor Lasers
2. Machine Learning Based Laser Failure Mode Detection
3. A Hybrid CNN-LSTM Approach for Laser Remaining Useful Life Prediction
4. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
5. Nonlinear principal component analysis using autoassociative neural networks
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