70 citations · 305 across the 27 of their papers we have counts for
4 papers · 1 filter
Gradient-free training of autoencoders for non-differentiable communication channels
Ognjen Jovanovic, Metodi Plamenov Yankov, Francesco Da Ros +1
Training of autoencoders using the back-propagation algorithm is challenging for non-differential channel models or in an experimental environment where gradients cannot be compute…
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…
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…
Probabilistically Shaped 4-PAM for Short-Reach IM/DD Links with a Peak Power Constraint
Thomas Wiegart, Francesco Da Ros, Metodi Plamenov Yankov +3
Probabilistic shaping for intensity modulation and direct detection (IM/DD) links is discussed and a peak power constraint determined by the limited modulation extinction ratio (ER…