A Neural Network-Based Harmonic Suppression Algorithm for Medium-to-High Resolution ADCs

This paper proposes a novel high-precision ADC digital calibration algorithm based on neural network (NN). The algorithm is to suppress the harmonic distortion caused by the non-ideal factors in ADC. As a result, regardless of the non-ideal types, it can be universally used as a back-end calibration black box in various ADC structures. A 14-bit ADC with trained NN reaches more than 12.3-bit of ENOB in behavioral simulation. We also applied the NN to a practical 12-bit sigma-delta ADC and achieved a significant improvement of more than 1-bit of ENOB.