Generalization Properties of Machine Learning-based Raman Models

U. C. de Moura,Darko Zibar,A. Margareth Rosa Brusin,Andrea Carena,Francesco Da Ros

2021 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC)（2021）

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Abstract

We investigate the generalization capabilities of neural network-based Raman amplifier models. The new proposed model architecture, including fiber parameters as inputs, can predict Raman gains of fiber types unseen during training, unlike previous fiber-specific models. (C) 2021 The Author(s)

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Key words

models,generalization,learning-based

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