Systems and methods for tuning and measuring a device under test using machine learning

Abstract

A test and measurement system includes a test and measurement instrument, including a port to receive a signal from a device under test (DUT), and one or more processors, configured to execute code that causes the one or more processors to: adjust a set of operating parameters for the DUT to a first set of reference parameters; acquire, using the test and measurement instrument, a waveform from the DUT; repeatedly execute the code to cause the one or more processors to adjust the set of operating parameters and acquire a waveform, for each of a predetermined number of sets of reference parameters; build one or more tensors from the acquired waveforms; send the one or more tensors to a machine learning system to obtain a set of predicted optimal operating parameters; adjust the set of operating parameters for the DUT to the predicted optimal operating parameters; and determine whether the DUT passes a predetermined performance measurement when adjusted to the set of predicted optimal operating parameters.

Dependencies are inferred from the claim text.