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Neural Network Training Framework for Nonlinear Signal-to-Noise Ratio Estimation in Heterogeneous Optical Networks

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Abstract

A computationally efficient framework is presented for calculating features used for training an ANN-based estimator of the nonlinear SNR in heterogeneous networks. Its efficacy is demonstrated using data computed for 153,576 distinct system configurations.

© 2021 The Author(s)

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