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- W3130052690 abstract "We propose a data augmentation technique to improve performance and decrease complexity of the supervised learning of nonlinearity compensation algorithms. We demonstrate both numerically and experimentally that the augmentation allows reducing the training dataset size up to 6 times while keeping the same post-compensation bit-error rate." @default.
- W3130052690 created "2021-03-01" @default.
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- W3130052690 date "2020-12-01" @default.
- W3130052690 modified "2023-09-23" @default.
- W3130052690 title "Simplifying the Supervised Learning of Kerr Nonlinearity Compensation Algorithms by Data Augmentation" @default.
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- W3130052690 doi "https://doi.org/10.1109/ecoc48923.2020.9333417" @default.
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