Abstract:
A test and measurement instrument includes an input configured to receive an input signal from a device under test (DUT), an output display, and one or more processors configured to execute code that causes the one or more processors to measure a noise component of the input signal, compensate the measured noise component based on the measurement population and a relative amount of noise generated by the test and measurement instrument and a total noise measurement, and produce the compensated measured noise component as a noise measurement on the output display. Methods 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.
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:
A method determines scattering parameters, S-parameters, for a device under test for a first frequency range. The method includes receiving S-parameters for the device under test for a second frequency range, the second frequency range greater than the first frequency range. Generally, the S-parameters for the device under test for the second frequency range can be determined using known methods. The method further includes measuring an actual response of the device under test, determining a desired signal of the device under test, and determining the S-parameters for the device under test for the first frequency range based the S-parameters for the second frequency range, actual response of the device under test and the desired signal of the device under test.
Abstract:
A test and measurement system includes a test and measurement device, a connection to allow the test and measurement device to connect to an optical transceiver, and one or more processors, configured to execute code that causes the one or more processors to: set operating parameters for the optical transceiver to reference operating parameters; acquire a waveform from the optical transceiver; repeatedly execute the code to cause the one or more processors to set operating parameters and acquire a waveform, for each of a predetermined number of sets of reference operating 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 operating parameters; set the operating parameters for the optical transceiver to the predicted operating parameters; and test the optical transceiver using the predicted operating parameters.
Abstract:
Disclosed is a mechanism for limiting Intersymbol Interference (ISI) when measuring uncorrelated jitter in a test and measurement system. A waveform is obtained that describes a signal. Such waveform may be obtained from memory. A processor then extracts a signal pulse from the waveform. The processor selects a window function based on a shape of the signal pulse. Further, the processor applies the window function to the signal pulse to remove ISI outside a window of the window function while measuring waveform jitter. The window function may be applied by applying the window function to the signal pulse to obtain a target pulse. A linear equalizer is then generated that results in the target pulse when convolved with the signal pulse. The linear equalizer is then applied to the waveform to limit ISI for jitter measurement.
Abstract:
A serial data link measurement and simulation system for use on a test and measurement instrument presents on a display device. A main menu having elements representing a measurement circuit, a simulation circuit and a transmitter. The main menu includes processing flow lines pointing from the measurement circuit to the transmitter and from the transmitter to the simulation circuit. The main menu includes a source input to the measurement circuit and one or more test points from which waveforms may be obtained. The simulation circuit includes a receiver. The measurement and simulation circuits are defined by a user, and the transmitter is common to both circuits so all aspects of the serial data link system are tied together.
Abstract:
A de-embed probe, including two inputs configured to connect to a device under test, a memory, a signal generator configured to output a signal, a plurality of load components, a plurality of switches, and a controller. Each load component is configured to provide a different load. A first switch of the plurality of switches is associated with the signal generator and the other switches of the plurality of switches are each associated with one load component. The controller is configured to control the plurality of switches to connect combinations of the loads from the plurality of load components and the signal from the signal generator across the two inputs.
Abstract:
An apparatus and method for splitting a wide band input signal and overlaying multiple frequency bands on each path associated with one or more digitizers. All frequencies from the split signal on each path can be fed to a mixer. The local oscillator of each mixer receives a sum of signals, which can each be set to any arbitrary frequency, as long as an associated matrix determinant of coefficients is non-zero. Each oscillator signal is multiplied by a coefficient, which can represent phase and magnitude, prior to summing the oscillator signals together. Each mixer mixes a combined signal with the input, thereby generating a set of multiple overlaid frequency bands. The digitized signals are processed to substantially reconstruct the original input signal. Thus, the wide band input signal is digitized using multiple individual digitizers. In particular, a system can support two wide band signals using four digitizers of narrower bandwidth.
Abstract:
A margin tester includes one or more ports to allow the margin tester to connect to a device under test (DUT), a memory, the memory containing a margin tester signature, a transmitter, a receiver to receive signals from the DUT, one or more processors configured to execute code that causes the one or more processors to: receive multiple signals from the receiver through the one or more ports, generate a performance indicator from the multiple signals, send the performance indicator and the margin tester signature to one or more machine learning networks, and receiving a result from the one or more machine learning networks containing a performance measurement prediction for the DUT.