Abstract: A test and measurement system includes a plurality of nodes, one or more nodes comprising sensors configured to receive signals, one or more generative adversarial network (GAN) models, one or more signal generators configured to generate and transmit signals, and one or more processors configured to execute code to cause the one or more processors to receive a request for a signal having a signal profile from a node of the plurality of nodes, send the signal profile and the request to one of the one or more GAN models, receive a matching signal profile that matches the signal profile, and transmit the matching signal profile to one of the one or more signal generators to generate and transmit a matching signal.

Abstract: A method of generating a calibration signal includes setting a first parameter to an initial first value and a second parameter to an initial second value, generating an initial eye diagram using the initial first value and the initial second value, determining a first difference between a first dimension of the initial eye diagram and a target first dimension, and a second difference between a second dimension of the initial eye diagram and a second target dimension, estimating a next first value to cause the first difference to be zero, setting the first parameter to the next first value, generating a next eye diagram, repeating the estimating, setting, and generating until the first dimension of a most recent next eye diagram is within the first target dimension, setting a final first parameter value to a most recent next first value, setting a final second parameter value to the initial second value when the second dimension of the most recent next eye diagram is within the second target dimension, genera

Abstract: A method of automatically selecting a continuous time linear equalization (CTLE) filter includes capturing a response waveform for a channel of a communication link of a device under test (DUT), generating a set of candidate CTLEs, and automatically selecting the CTLE from the set of candidate CTLEs using the response waveform. A test and measurement instrument has a user interface, a port to allow the instrument to connect to a device under test (DUT), and one or more processors configured to execute code to cause the one or more processors to: generate a set of CTLE candidates; capture a response waveform for the channel; and automatically select the CTLE from the set of candidate CTLEs using the response waveform.

Abstract: A test and measurement instrument has a port to receive a signal from a device under test (DUT), one or more processors configured to execute code that causes the one or more processors to acquire a waveform from the signal, derive a pattern waveform from the waveform using one of either hardware or software clock recovery, perform linear fit pulse response (LFPR) extractions on the pattern waveform to extract more than one LFPR, determine a reference pulse response from the more than one LFPRs, compare at least one of the LFPRs to the reference pulse response to determine a difference, and tune the DUT to reduce the difference. The test and measurement instrument may also use the multiple LFPRs as an input to a machine learning network to perform measurement predictions for the DUT.

Abstract: A method of automatically selecting a continuous time linear equalization (CTLE) filter includes capturing a response waveform for a channel of a communication link of a device under test (DUT), generating a set of candidate CTLEs, and automatically selecting the CTLE from the set of candidate CTLEs using the response waveform. A test and measurement instrument has a user interface, a port to allow the instrument to connect to a device under test (DUT), and one or more processors configured to execute code to cause the one or more processors to: generate a set of CTLE candidates; capture a response waveform for the channel; and automatically select the CTLE from the set of candidate CTLEs using the response waveform.

Abstract: A method of generating a calibration signal includes setting a first parameter to an initial first value and a second parameter to an initial second value, generating an initial eye diagram using the initial first value and the initial second value, determining a first difference between a first dimension of the initial eye diagram and a target first dimension, and a second difference between a second dimension of the initial eye diagram and a second target dimension, estimating a next first value to cause the first difference to be zero, setting the first parameter to the next first value, generating a next eye diagram, repeating the estimating, setting, and generating until the first dimension of a most recent next eye diagram is within the first target dimension, setting a final first parameter value to a most recent next first value, setting a final second parameter value to the initial second value when the second dimension of the most recent next eye diagram is within the second target dimension, genera