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A Performance Optimization Method for Learned Digital Backpropagation to Select the Optimal Power(s) of Training Data

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Abstract

A method is proposed to select the optimal power(s) of training data for learned digital backpropagation (LDBP): Low-step LDBP should be trained on multi-power data, while high-step LDBP should be trained on high single-power data.

© 2021 The Author(s)

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