Flexible Raman Amplifier Optimization Based on Machine Learning-Aided Physical Stimulated Raman Scattering Model
Author:
Affiliation:
1. Department of Electrical and Photonics Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark
2. Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy
Funder
Danish National Research Foundation Centre of Excellence SPOC
Villum YI
OPTIC-AI
European Research Council
Ministero dell’Istruzione, dell’Università e della Ricerca
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atomic and Molecular Physics, and Optics
Link
http://xplorestaging.ieee.org/ielx7/50/10016253/09932879.pdf?arnumber=9932879
Reference31 articles.
1. Optimal Design of Gain-Flattened Raman Fiber Amplifiers Using a Hybrid Approach Combining Randomized Neural Networks and Differential Evolution Algorithm
2. Spectral and Spatial Power Evolution Design With Machine Learning-Enabled Raman Amplification
3. Model-Aware Deep Learning Method for Raman Amplification in Few-Mode Fibers
4. Robust, compact, and flexible neural model for a fiber Raman amplifier
5. SNR Optimization of Multi-Span Fiber Optic Communication Systems Employing EDFAs With Non-Flat Gain And Noise Figure
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