Statistical neural network (SNN) for predicting signal-to-noise ratio (SNR) from static parameters and its validation in 16-bit, 125-MSPS analog-to-digital converters (ADCs).

In the analog-to-digital converter (ADC) test process, the static and dynamic performance parameters are the most important, and the tests for these parameters account for the bulk of the ADC test cost. These two types of parameters follow certain relationships, which are incorporated into the ADC test to reduce the cost. In this paper, we focus on the signal-to-noise ratio (SNR), a key indicator of the dynamic performances of ADCs.