Machine Learning Enabled Directly Modulated Lasers - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

Machine Learning Enabled Directly Modulated Lasers

Résumé

The complex dynamics of systems based on directly modulated lasers (DMLs) can hinder their optimization, as their simulation entails numerical methods where gradient calculation is not readily available. Our proposed solution combines data-driven DML modeling with end-to-end (E2E) learning techniques to obtain optimal link configurations.
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Dates et versions

hal-04704340 , version 1 (20-09-2024)

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Sergio Hernandez Fernandez, Christophe Peucheret, Francesco da Ros, Darko Zibar. Machine Learning Enabled Directly Modulated Lasers. 2024 24th International Conference on Transparent Optical Networks (ICTON), Jul 2024, Bari, Italy. pp.1-1, ⟨10.1109/ICTON62926.2024.10648111⟩. ⟨hal-04704340⟩
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