3 papers
eess.SP2020
Power Evolution Prediction and Optimization in a Multi-span System Based on Component-wise System Modeling
Metodi P. Yankov, Uiara Celine de Moura, Francesco Da Ros
Cascades of a machine learning-based EDFA gain model trained on a single physical device and a fully differentiable stimulated Raman scattering fiber model are used to predict and…
eess.SP2020
Machine learning-based EDFA Gain Model Generalizable to Multiple Physical Devices
Francesco Da Ros, Uiara Celine de Moura, Metodi P. Yankov
We report a neural-network based erbium-doped fiber amplifier (EDFA) gain model built from experimental measurements. The model shows low gain-prediction error for both the same de…
physics.app-ph2019
Experimental demonstration of arbitrary Raman gain-profile designs using machine learning
Uiara C. de Moura, Francesco Da Ros, A. Margareth Rosa Brusin +2
A machine learning framework for Raman amplifier design is experimentally tested. Performance in terms of maximum error over the gain profile is investigated for various fiber type…