Abstract: A test and measurement instrument has an input configured to receive a signal from a device under test, a memory, a user interface to allow the user to input settings for the test and measurement instrument, and one or more processors, the one or more processors configured to execute code that causes the one or more processors to: acquire a waveform representing the signal received from the device under test; generate one or more tensor arrays based on the waveform; apply machine learning to the one or more tensor arrays to produce equalizer tap values; and apply equalization to the waveform using the equalizer tap values to produce an equalized waveform; and perform a measurement on the equalized waveform to produce a value related to a performance requirement for the device under test.

Abstract: A test and measurement device includes one or more ports configured to connect to a device under test (DUT), a time domain reflectometry (TDR) source configured receive a source control signal and to produce an incident signal to be applied to the DUT, one or more analog-to-digital converters (ADC) configured to receive a sample clock and sample the incident signal from the TDR source and a time domain reflection (TDR) signal or a time domain transmission (TDT) signal from the DUT to produce an incident waveform and a TDR/TDT waveform, one or more processors configured to execute code to cause the one or more processors to: control a clock synthesizer to produce the sample clock and the source control signal, and use a period of the TDR source, a period of the sample clock, and the number of samples to determine time locations for samples in the incident waveform and the TDR/TDT waveform, and a display configured to display the incident waveform and the TDR/TDT waveform.

Abstract: A test and measurement instrument includes a user interface, one or more probes to connect to a device under test (DUT), and one or more processors to take measurements during application of a double pulse test to the DUT to create measurement data, identify a measurement start point, find a measurement stop point, use the measurement data between the measurement start point and the measurement stop point to determine an output charge, Qoss, of the DUT, and display the output charge to a user. A method of determining output charge of a device under test (DUT) includes taking measurements during application of a double pulse test to create measurement data, identifying a measurement start point, finding a measurement stop point, using the measurement data between the measurement start point and the measurement stop point to determine an output charge, Qoss, of the DUT, and displaying the output charge.

Abstract: A test and measurement device includes an input configured to receive an analog signal from a Device Under Test (DUT), an Analog to Digital Converter (ADC) coupled to the input and structured to convert the analog signal to a digital signal, a receiver implemented in a first Field Programmable Gate Array (FPGA) and structured to accept the digital signal and perform signal analysis on the digital signal, a transmitter implemented in a second FPGA and structured to generate a digital output signal, and a Digital to Analog Converter (DAC) coupled to the transmitter and structured to convert the digital output signal from the transmitter to an analog signal, and structured to send the analog signal to the DUT. The receiver and the transmitter are coupled together by a high speed data link over which data about the current testing environment may be shared.

Abstract: A current measurement device includes a shunt having sense leads, the shunt configured to be located in a current path for a current to be measured, and a Rogowski coil at least partially wrapped around the shunt, the current measuring device configured to combine signals from the shunt and the Rogowski coil. A current measurement device includes a shunt having sense leads configured to be located in a current path for a current to be measured, a Rogowski coil in series with the sense leads and at least partially wrapped around the shunt, a compensating pole connected to the Rogowski coil, and an isolation barrier connected to the compensating pole.

Abstract: A system for measuring characteristics of wide bandgap Devices Under Test (DUTs) includes a testing fixture including one or more wide bandgap DUTs, and a measurement instrument having one or more processors configured to apply a stimulus to provoke a response of one or more wide bandgap DUTs, measure the response, graph the response on one or more displays, each display having a vertical scale, and automatically adjusting the vertical scale of the one or more displays until no clipping occurs in the one or more displays. Methods of dynamically configuring a test and measurement instrument based on a particular testing setup are also described.

Abstract: A communication system includes one or more transmitters, each transmitter to: transmit communication signals using a defined signaling protocol with multiple antenna elements to a target receiver, the communication signals containing known specific transmit sequences spread across a frequency spectrum of the communication signals to be detectable only by receivers having the known specific transmit sequences, and receive feedback from the target receiver indicating any errors in reception of the communication signals based upon the known specific transmit sequences, and a machine learning system to use configuration of the multiple antenna elements when the communication signal was sent and the feedback to predict preconfigured settings for transmitters.

Abstract: A test and measurement instrument has an acquisition system to receive and digitize a batch of waveforms into a batch of digitized waveforms, a memory configured as a raster plane having rows and columns, a graphics processing unit (GPU) capable of processing multiple threads to rasterize the batch of digitized waveforms to the raster plane to form a batch histogram and to group multiple threads into groups of a first type of group, assign each thread group of the first type of group to one column in the raster plane, execute a common instruction per thread group of the first type to populate the raster plane, and transfer the batch histogram upon completion, and a central processing unit (CPU) to receive the batch histogram from the GPU, and display a map of the batch histogram on a display.

Abstract: A test and measurement system includes a test and measurement instrument configured to receive waveform data from a device under test (DUT) on a manufacturing line, a machine learning system connected to the test and measurement instrument, and one or more processors configured to execute code that causes the one or more processors to: collect optimal tuning parameter data sets from the DUT after the DUT is tuned on the manufacturing line, determine one or more parameter data sets from the optimal tuning parameter data, load the one or more parameter data sets into the DUT, collect waveform data from the DUT for the one or more parameter data sets as training data sets, train the machine learning system using the training data sets, and use the machine learning system after training to produce an output related to the DUT.

Abstract: A test and measurement instrument has an arbitrary waveform generator having at least two waveform generators. Each waveform generator includes a signal generator to generate in-phase (I) and quadrature (Q) digital signals according to a selected signal type for a digital constituent output signal, a pulse envelope sequencer to modulate amplitude of the I and Q digital signals, and one or more multipliers to combine the I and Q digital signals with a carrier signal to produce the digital constituent output signal. The arbitrary waveform generator includes a stream manager to produce modulation descriptor words for the waveform generators, a summing block to selectively combine digital constituent output signals to produce a digital multi-constituent output signal, a digital-to-analog converter to convert the digital multi-constituent output signal to an analog output signal, and an internal signal analyzer to receive an analyzer input of one of more of the digital output signals.

Abstract: A test and measurement instrument includes an input configured to accept an input signal from a Device Under Test, an acquisition memory handler structured to store the input signal as a series of digital samples in an acquisition memory, and a rasterizer structured to generate a histogram of the values of the digital samples prior to or simultaneously with the values being stored in the acquisition memory. Methods of generating a raster display from a series of digital samples from an input display are also described.

Abstract: A system for determining an amount of time skew between two measurement probes includes a first probe and a second probe and one or more processors configured to measure a current signal from a Device Under Test (DUT) through the first probe, measure a voltage signal from the DUT through the second probe, generate a modeled voltage signal from the measured current signal, compare the modeled voltage signal to the measured voltage signal, and determine the amount of time skew between the first and the second probe from the compared signals. Methods are also described.

Abstract: A test and measurement system has a test and measurement instrument having an adaptor with an interface configured to communicate through one or more communications links with a new device under test to receive new test results, a memory configured to store a database of test results and a database of analyzed test results related to tests performed with one or more prior devices under test, a data analyzer connected to the test and measurement instrument through the one or more communications link, the data analyzer configured to analyze the new test results based on the stored test results, and a health score generator configured to generate a health score for the new device under test based on the analysis from the data analyzer.

Abstract: A current sensor configured to measure current in a current-carrying conductor. The current sensor includes a shunt configured to be placed in series with the current-carrying conductor, and a Rogowski coil including at least one conductor segment. The shunt and the Rogowski coil are coupled to produce an output signal representing the current in the current-carrying conductor.

Abstract: Disclosed is a signal isolating test instrument, such as an electronics test probe. The instrument includes an input to receive a floating analog signal. An upconverter is employed to modulate the floating analog signal to a microwave frequency analog signal. An isolation barrier prevents coupling of the floating analog signal to an earth ground. The instrument employs a microwave structure to transmit the microwave frequency analog signal across the isolation barrier via electromagnetic coupling. A downconverter is then employed to demodulate the microwave frequency analog signal to obtain a ground referenced test signal corresponding to the floating analog signal.

Abstract: A test and measurement instrument has one or more ports configured to receive a signal one or more devices under test (DUT), and 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, perform linear response extraction on the pattern waveform, present one or more data representations including a data representation of the extracted linear response to a machine learning system, and receive a prediction for a measurement from the machine learning system. A method of performing a measurement on a waveform includes acquiring the waveform at a test and measurement device, deriving a pattern waveform from the waveform, performing linear response extraction on the pattern waveform, presenting one or more data representations including a data representation of the extracted linear response to a machine learning system, and receiving a prediction of the measurement from the machine learning system.

Abstract: A test and measurement instrument has an input port to allow the instrument to receive one or more waveforms from a device under test (DUT), one or more low pass filters to remove a portion of the noise from the one or more waveforms, and one or more processors to: select a waveform pattern from the waveforms, measure noise in the one or more waveforms and generate a noise representation of the noise removed, create one or more images using the waveform pattern and the one or more filtered waveforms, add the noise representation to the one or more images to produce at least one combined image, input the at least one combined image to one or more deep learning networks, and receive one or more predicted values for the DUT.

Abstract: A system includes an input for accepting a dataset including at least two sets of data in a dataset domain and one or more processors configured to derive at least two principal components from the dataset using principal component analysis, the at least two principal components being orthogonal to one another, map the dataset to a principal component domain derived from the at least two principal components, generate additional data in the principal component domain, and remap the additional data in the principal component domain back to the dataset domain as a newly generated dataset. Methods of operation and description of storage media, the operation of which performs the above operations, are also described.

Abstract: A system includes an input for accepting an input signal from a Device Under Test (DUT), a measurement unit for generating first measurement data and second measurement data from the input signal, and one or more processors configured to derive at least one principal component from the first and second measurement data using principal component analysis, and remap the first measurement data and the second measurement data to a principal component domain derived from the at least one principal component. Methods of operation and description of storage media, the operation of which performs the above operations, are also described.

Abstract: A test and measurement instrument includes one or more ports to connect to one or more devices under test (DUT) having tuning screws, and to a robot, one or more processors to configured to: send commands to the robot to position the tuning screws on the one or more DUTs to one or more sets of positions, each set of positions being a parameter set for the tuning screws, acquire a set of operating parameters for each parameter set from the one or more DUTs, generate a parameter set image for each set, create a combined image of the parameter set images, provide the combined image to a machine learning system to obtain a predicted set of values, adjust the predicted set of values to produce a set of predicted positions, send commands to the robot to position the tuning screws to positions in the set of predicted positions, obtain a set of tuned operating parameters from the one or more DUTs, and validate operation of the one or more DUTs.