Deep learning based method and device for noise suppression and distortion correction of analog-to-digital converters

Abstract

A method for noise suppression and distortion correction of analog-to-digital converters based on deep learning that realizes effect of correcting noise and distortion of analog to digital converters. The method is applied to electronic ADCs or photonic ADCs. It utilizes the learning ability of the deep network to perform system response learning on ADCs which need noise suppression and distortion correction, establishes a computational model in the deep network that can suppress the reconstruction of noises and distorted signals, performs noise suppression and distortion correction on the signals obtained by ADCs, and thereby improves performance of the learned ADCs. The present invention has a very important role in improving the performance of the microwave photon system with high sampling precision of microwave photon radar and optical communication system.

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