18 citations · 18 across the 2 of their papers we have counts for
5 papers
Simultaneous gain profile design and noise figure prediction for Raman amplifiers using machine learning
Uiara Celine de Moura, Ann Margareth Rosa Brusin, Andrea Carena +2
A machine learning framework predicting pump powers and noise figure profile for a target distributed Raman amplifier gain profile is experimentally demonstrated. We employ a singl…
Experimental characterization of Raman amplifier optimization through inverse system design
Uiara Celine de Moura, Francesco Da Ros, Ann Margareth Rosa Brusin +2
Optical communication systems are always evolving to support the need for ever-increasing transmission rates. This demand is supported by the growth in complexity of communication…
Multi-band programmable gain Raman amplifier
Uiara Celine de Moura, Md Asif Iqbal, Morteza Kamalian +7
Optical communication systems, operating in C-band, are reaching their theoretically achievable capacity limits. An attractive and economically viable solution to satisfy the futur…
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…
An ultra-fast method for gain and noise prediction of Raman amplifiers
Ann Margareth Rosa Brusin, Vittorio Curri, Darko Zibar +1
A machine learning method for prediction of Raman gain and noise spectra is presented: it guarantees high-accuracy (RMSE < 0.4 dB) and low computational complexity making it suitab…