A multi-layer neural network is employed to learn the mapping between Raman gain profile and pump powers and wavelengths. The learned model predicts with high-accuracy, low-latency and low-complexity the pumping setup for any gain profile.
Machine learning-based Raman amplifier design / Zibar, D.; Ferrari, A.; Curri, V.; Carena, A.. - ELETTRONICO. - M1J.1(2019), pp. 1-3. ((Intervento presentato al convegno OFC 2019 tenutosi a San Diego (CA) nel 3–7 March 2019.
Titolo: | Machine learning-based Raman amplifier design |
Autori: | |
Data di pubblicazione: | 2019 |
Abstract: | A multi-layer neural network is employed to learn the mapping between Raman gain profile and pump... powers and wavelengths. The learned model predicts with high-accuracy, low-latency and low-complexity the pumping setup for any gain profile. |
ISBN: | 978-1-943580-53-8 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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OFC_2019_paper_on_Design_of_Raman_amplifiers_using_ML.pdf | Articolo principale | 1. Preprint / Submitted Version | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
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http://hdl.handle.net/11583/2738993
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