Abstract: A test and measurement probe system, including an input to receive an input signal, the input signal including a low frequency (LF) and/or direct current (DC) component and an alternating current (AC) component, an extractor circuit, such as an AC coupling circuit or a LF and/or DC rejection circuit, configured to receive the input signal and to separate the AC component and the LF and/or DC component from the input signal, a first output to output the alternating current component to the test and measurement instrument, and a second output to output the direct current component to the test and measurement instrument. In some embodiments, the LF and/or DC component is digitized prior to being output by the second output.

Abstract: A test and measurement instrument includes a first channel input for accepting a first input signal, a second channel input for accepting a second input signal, a spectrogram processor for producing a first spectrogram from the first input signal and for producing a second spectrogram from the second input signal, and a display for simultaneously showing the first spectrogram and the second spectrogram. Methods are also described.

Abstract: A test and measurement instrument includes components and methods for measuring noise at an output of a power supply, measuring jitter of a serial data signal produced by a data generating circuit coupled to the power supply and correlating the noise measured from the power supply to the jitter of the serial data signal. The correlation may be performed in the frequency domain. Spectral plots of the measured noise and the measured jitter may be generated and presented to the user.

Abstract: A test and measurement system has one or more inputs connectable to a device under test (DUT), and one or more processors configured to execute code that causes the one or more processors to: gather a set of training waveforms by acquiring one or more waveforms from one or more DUTs or from simulated waveforms, remove noise from the set of training waveforms to produce a set of noiseless training waveforms, and use the set of noiseless training waveforms as a training set to train a neural network to predict a measurement value for a DUT, producing a trained neural network.

Abstract: A structure has a flexible thermally conductive material having an adhesive surface and a non-adhesive surface, and a thermally conductive adhesive adhered to the adhesive surface of the flexible thermally conductive material leaving the non-adhesive surface exposed to an atmosphere in which the structure resides. A structure has a substrate having one or more conductive paths, and a flexible, thermally conductive material attached to at least a portion of the substrate to draw heat away from the conductive paths. An apparatus has a substrate having one or more conductive paths, a probe tip at one end of the substrate configured to electronically connect with a device under test, and a flexible, thermally conductive material attached to at least a portion of the substrate to draw heat away from the probe tip and conductive paths.

Abstract: A system to develop and test machine learning models has a waveform emulator machine learning system, a user interface to allow a user to input one or more design parameters for the waveform emulator machine learning system, one or more processors configured to execute code to cause the one or more processors to: send the one or more design parameters to the waveform emulator machine learning system; receive one or more data sets from the waveform emulator machine learning system, the one or more data sets based on the one or more design parameters; train a developed machine learning model using at least one of the one or more data sets, resulting in a trained machine learning model; validate the trained machine learning model using a previously unused one of the one or more data sets; adjust the trained machine learning model as needed; and repeat the training, validating, and adjusting until an optimal machine learning model is trained.

Abstract: A test and measurement device includes an input port to receive an input signal, a sampling circuit structured to generate a sample from the input signal, in which generating the sample from the input signal produces an amount of kickout energy, and an energy reducing circuit coupled between the sampling circuit and one or more other components of the test and measurement device, the energy reducing circuit structured to decrease the amount of kickout energy from the sampling circuit. The energy reducing circuit may include or be combined with a pick-off circuit. Methods are also described.

Abstract: A test and measurement instrument including a display and one or more processors configured to display on the display a waveform viewing area with a vertical dimension and an adjustable horizontal dimension, the test and measurement instrument configured to display one or more waveforms in the waveform viewing area, a global settings readout bar located vertically adjacent to the waveform viewing area, the global settings readout bar including a first selectable information badge, wherein when the first selectable information badge is selected, displaying a first menu originating from the first selectable information badge to modify a setting of the test and measurement instrument related to the first selectable information badge. The first selectable information badge including a warning indicator when an error or safety condition occurs.

Abstract: A test and measurement device has a port to receive a signal from a device under test (DUT), one or more analog-to-digital converters (ADC) to digitize the signal to create one or more waveforms, a display, and one or more processors configured to execute code that causes the one or more processors to: generate a histogram from the waveform, the histogram having one or more dimensions; and calculate one or more entropy values for each of the one or more dimensions. A method includes receiving a signal from a device under test (DUT) at a test and measurement device, digitizing the signal using one or more analog-to-digital converters (ADC) to produce a waveform, generating a histogram from the waveform, the histogram having one or more dimensions, and calculating one or more entropy values for each of the one or more dimensions,.

Abstract: Methods and devices for digitizing an analog repetitive signal using waveform averaging are described. An example method includes generating a discrete set of analog dither offset voltages, wherein at least two of the discrete set of analog dither offset voltages are different from each other, receiving the analog repetitive signal comprising multiple instances of a waveform, wherein the waveform has a waveform duration, generate a timing alignment to align each waveform of the analog repetitive signal and the corresponding analog dither offset voltage over the waveform duration, combining, based on the timing alignment, each waveform and the corresponding analog dither offset voltage over the waveform duration to produce an analog output signal, converting the analog output signal to a digital output signal, and producing, based on the timing alignment, a digital averaged signal based on averaging the multiple instances of the waveform in the analog output signal.

Abstract: A test and measurement system can include a data store configured to store augmentation settings for dynamically augmenting a physical testing environment and a computing device coupled to the data store. The computing device can be configured to receive an input feed from the physical testing environment, create an augmentation image based on the augmentation settings and the input feed, and output the augmented image to be overlaid on the physical testing environment to augment a user's view of the physical testing environment.

Abstract: A test and measurement instrument has a user interface, one or more probes 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: receive waveform data from the DUT after activation of the DUT by application of power from a power supply, and application of at least a first and second pulse from a source instrument, locate one or more reverse recovery regions in the waveform data, determine a reverse recovery time for the DUT from the reverse recovery region, and display a reverse recovery plot of the one or more reverse recovery regions on the user interface, the reverse recovery plot being automatically configured to display one or more of the reverse recovery regions, and including at least one characteristic for the one or more reverser recovery regions annotated on the reverse recovery plot.

Abstract: A test and measurement instrument has a user interface, one or more probes 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: receive one or more user inputs through the user interface, at least one of the user inputs to identify at least one analysis to be performed on the DUT, receive waveform data from the DUT when the DUT is activated by application of power from a power supply, and application of one of a first and second pulse or multiple pulses from a source instrument, perform the at least one analysis on the waveform data, and display the waveform data and analysis on the user interface.

Abstract: A test and measurement probe system (100,104), including an input (106) to receive an input signal, the input signal including a low frequency (LF) and/or direct current (DC) component and an alternating current (AC) component, an extractor circuit (110), such as an AC coupling circuit or a LF and/or DC rejection circuit, configured to receive the input signal and to separate the AC component and the LF and/or DC component from the input signal, a first output (118) to output the alternating current component to the test and measurement instrument, and a second output to output the direct current component to the test and measurement instrument. In some embodiments, the LF and/or DC component is digitized prior to being output by the second output.

Abstract: A test and measurement device includes an input for receiving a test waveform from a Device Under Test (DUT), where the test waveform has a plurality of input level transitions, a selector structured to respectively and individually extract only those portions of the test waveform that match two or more predefined patterns of input level transitions of the test waveform, a noise compensator structured to individually determine and remove, for each of the extracted portions of the waveform, a component of a jitter measurement caused by random noise of the test and measurement device receiving the test waveform, a summer structured to produce a composite distribution of timing measurements with removed noise components from the extracted portions of the test waveform, and a jitter processor structured to determine a first noise-compensated jitter measurement of the DUT from the composite distribution. Methods of determining noise-compensated jitter measurements are also disclosed.

Abstract: A test and measurement instrument for measuring a current in a device under test, comprising an input configured to receive signals from a magnetic field probe; and one or more processors configured to measure, from a signal from the magnetic field probe, a magnetic field generated by a current-carrying conductor of the device under test based on a known current, determine a calibration factor based on the known current and the magnetic field, and generate a calibrated measurement of an unknown current in the current-carrying conductor using a magnetic field generated by the current-carrying conductor based on the unknown current and the calibration factor.

Abstract: An accessory device has a test port, an instrument port to connect to an instrument having an operating bandwidth, and one or more configurable signal paths connectable between the test port and the instrument port to convert a signal from the test port having a first frequency range to a signal having a second frequency range different than the first frequency range. A test and measurement system has a test and measurement instrument having an operating bandwidth, and an accessory device. The accessory device has a first instrument port to connect the accessory device to the test and measurement instrument, a test port to connect the accessory device to a device under test, and one or more configurable signal paths connectable between the test port and the instrument port to down-convert a signal from the test port having a first frequency range to a signal having a second frequency range lower than the first frequency range.

Abstract: A test and measurement machine learning model development system includes a user interface, one or more ports to allow the system to connect to one or more data sources, one or more memories, and one or more processors configured to execute code to cause the one or more processors to: display on the user interface one or more application user interfaces, the application user interfaces to allow a user to provide user inputs; use and application programming interface to configure the system based on the user inputs; receive data from the one or more data sources; apply one or more modules from a library of signal processing and feature extraction modules to the data to produce training data; apply one or more machine learning models to the training data; provide monitoring of the one or more machine learning models; and save the one or more machine learning models to at least one of the one or more memories.

Abstract: A test and measurement device has an interface, one or more connectors, each connector to allow the test and measurement device to connect to a test and measurement instrument, and one or more processors, the one or more processors configured to execute code to cause the one or more processors to: receive one or more user inputs through the interface identifying one or more tests to perform on a device under test (DUT); form a connection through one of the one or more connectors to the DUT to perform the one or more tests and receive test result data; apply one or more machine learning models to the test result data to identify potentially anomalous test results; and generate and present a representation of the test result data and the potentially anomalous test results.

Abstract: A test and measurement device has an input port configured to receive a signal from a device under test, the signal having a symbol rate, one or more analog-to-digital converters to convert the signal to waveform samples at a sampling rate, and one or more processors configured to execute code that, when aliasing is present in the waveform samples, causes the one or more processors to: up-sample the waveform samples to produce up-sampled samples; use the up-sampled samples to produce a real-time waveform; perform clock recovery on the real-time waveform to produce a recovered clock; and resample the waveform samples using the recovered clock to produce a non-aliased waveform.