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Device dependent distortion correction in time-stretch photonic analog to digital converters using deep neural networks

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Abstract

We experimentally demonstrate a novel deep learning-aided time-stretch photonic front end architecture to overcome device-dependent distortions to improve the signal-to-noise and distortion ratio by more than 24 dB, and reduce the bandwidth requirements of the back-end electronic ADC by three times.

© 2024 The Author(s)

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