Abstract: A phase-shifted sampling module for sampling a signal is described. The phase-shifted sampling module includes a primary sampler module, an ADC module, and an equalization module. The primary sampler module includes an analog signal input, a first signal path, and a second signal path. The equalization module includes a primary sampler equalizer sub-module. The primary sampler equalizer sub-module is configured to compensate low-frequency mismatches between the first signal path and the second signal path. Further, a method for determining filter coefficients of an equalization module of a phase-shifted sampling module is described.

Abstract: The present disclosure provides a main measurement device for simultaneously measuring signals with at least one secondary measurement device, the main measurement device comprising a reference signal output port configured to couple to the at least one secondary measurement device, a reference signal generator coupled to the reference signal output port and configured to generate a reference signal, a measurement port configured to receive a signal to be measured, a trigger output port configured to couple to a trigger input port of the at least one secondary measurement device and to output a trigger signal, and a controllably switchable internal signal path configured to selectively couple the reference signal generator with the measurement port. Further, the present invention discloses a respective secondary measurement device, a respective measurement system, and a respective method.

Abstract: The present invention relates to a method for training a signal characterization neural network. The method comprises the steps of: providing a measurement signal having at least one distortion; assigning at least one predefined signal integrity identifier to a corresponding distortion within the measurement signal; generating at least one input training vector based on the provided measurement signal and the corresponding assigned signal integrity identifier; and applying the generated input training vector on input terminals of the signal characterization neural network for training the signal characterization neural network. The present invention also relates to a method for automatically characterizing a measurement signal. The present invention further relates to a measurement apparatus and a corresponding method for analyzing a waveform signal.

Abstract: The present disclosure provides an analog-to-digital converter system comprising a sampler configured to sample an input signal and provide at least two output signals with a predetermined output sample rate, and an analog-to-digital converter for each one of the output signals and configured to convert the respective output signal into a digital signal with a predetermined converter sample rate, wherein the converter sample rate is higher than the output sample rate. Further, the present disclosure provides a respective method.

Abstract: The present disclosure provides a circuitry distortion corrector for correcting distortions of electrical signals. The circuitry distortion corrector comprises a first correction filter that filters the received signals, and a second correction filter that is coupled to the first correction filter and filters the signals that are filtered by the first correction filter. The first correction filter operates based on first filter coefficients that are based on first value tuples, each first value tuple comprising a first frequency and a respective first circuitry characterizing value, and wherein the first frequencies are equally spaced apart, and the second correction filter operates with second filter coefficients that are based on second value tuples, each second value tuple comprising a second frequency and a respective second circuitry characterizing value, wherein the second frequencies are logarithmically spaced apart.

Abstract: A measurement instrument for acquiring an input signal is described. The measurement instrument includes a first acquisition path with a first acquisition circuit having a first sampling rate. The measurement instrument includes at least one second acquisition path with a second acquisition circuit, having a second sampling rate. The measurement instrument is configured to acquire the input signal with an overall sampling rate being higher than the first sampling rate and the second sampling rate. The first acquisition path and the at least one second acquisition path each have a decimation filter and a decimator connected in series to the decimation filter, thereby equalizing a low frequency band in the input signal when processing the input signal. Further, method of acquiring an input signal is described.

Abstract: A measurement apparatus comprising an acquisition memory adapted to store data sections of at least one acquired measurement signal; a processor adapted to calculate a measurement parameter vector, v, for each data section of the acquired measurement signal; and a trained autoencoder neural network adapted to process the measurement parameter vectors, v, applied as input data to the trained autoencoder neural network to provide at a middle layer of said autoencoder neural network an encoded vector, h, with characteristic signal features of the acquired measurement signal.

Abstract: A method for operating an oscilloscope is described, wherein a waveform axis scale input value is detected. Further, a record length input value is detected. An oscilloscope operating point is determined relative to at least one predetermined operating mode limit. In addition, a method for operating an oscilloscope as well as an oscilloscope are described.

Abstract: A signal analyzer for analyzing a signal includes a frontend with at least two interleaved digitizers configured to digitize an input signal, thereby generating a digitized input signal. The signal analyzer also includes a first interleave alignment filter established by a hardware interleave alignment filter that is configured to hardware-compensate non-ideal effects of the frontend in the digitized input signal in real-time, thereby generating a hardware-compensated, digitized input signal. Further, the signal analyzer includes an acquisition memory configured to store the hardware-compensated, digitized input signal, thereby acquiring an acquired signal. Moreover, the signal analyzer includes a second interleave alignment filter configured to fine-compensate further non-ideal effects of the frontend in a post-processing of the acquired signal.

Abstract: A phase-shifted sampling module for sampling a signal is described. The phase-shifted sampling module includes a primary sampler module, an ADC module, and an equalization module. The primary sampler module includes an analog signal input, a first signal path, and a second signal path. The equalization module includes a primary sampler equalizer sub-module. The primary sampler equalizer sub-module is configured to compensate low-frequency mismatches between the first signal path and the second signal path. Further, a method for determining filter coefficients of an equalization module of a phase-shifted sampling module is described.

Abstract: A measurement instrument for testing a device under test is described. The device under test has at least two test points. The measurement instrument includes a first measurement channel, a second measurement channel, and a machine-learning circuit. The first measurement channel is configured to process a first input signal associated with one of the at least two test points, thereby generating a first measurement signal. The second measurement channel is configured to process a second input signal associated with another one of the at least two test points, thereby generating a second measurement signal. The machine-learning circuit is configured to determine at least one correlation quantity based on the first measurement signal and based on the second measurement signal, wherein the at least one correlation quantity is indicative of a correlation between the first measurement signal and the second measurement signal. Further, a measurement system and a signal processing method are described.

Abstract: The present disclosure provides a main measurement device for simultaneously measuring signals with at least one secondary measurement device, the main measurement device comprising a reference signal output port configured to couple to the at least one secondary measurement device, a reference signal generator coupled to the reference signal output port and configured to generate a reference signal, a measurement port configured to receive a signal to be measured, a trigger output port configured to couple to a trigger input port of the at least one secondary measurement device and to output a trigger signal, and a controllably switchable internal signal path configured to selectively couple the reference signal generator with the measurement port. Further, the present invention discloses a respective secondary measurement device, a respective measurement system, and a respective method.

Abstract: The present disclosure provides a circuitry distortion corrector for correcting distortions of electrical signals. The circuitry distortion corrector comprises a first correction filter that filters the received signals, and a second correction filter that is coupled to the first correction filter and filters the signals that are filtered by the first correction filter. The first correction filter operates based on first filter coefficients that are based on first value tuples, each first value tuple comprising a first frequency and a respective first circuitry characterizing value, and wherein the first frequencies are equally spaced apart, and the second correction filter operates with second filter coefficients that are based on second value tuples, each second value tuple comprising a second frequency and a respective second circuitry characterizing value, wherein the second frequencies are logarithmically spaced apart.

Abstract: A signal analysis method for analyzing a pulse modulated input signal is described. The signal analysis method includes: receiving the pulse modulated input signal, the input signal including a symbol sequence; recovering a clock signal from the input signal, the clock signal being associated with the input signal; sampling the input signal based on the clock signal, thereby obtaining a set of input signal samples, each of the input signal samples having a certain level being constant over time; determining at least two different levels of input signal samples being associated with different symbols of the symbol sequence; and determining at least one decision threshold based on the at least two different levels determined previously, the decision threshold being associated with a symbol transition of the symbol sequence. Further, a signal analysis apparatus is described.

Abstract: An electrical measurement device for measuring at least one electrical signal is described, the electrical measurement device comprising an electrical measurement unit for measuring the electrical signal and for deriving at least one measurement parameter from the measured electrical signal, an acoustic processing unit for processing a signal obtained from the electrical measurement unit, and a loudspeaker for outputting an acoustic signal representative of the signal obtained from the electrical measurement unit. The acoustic processing unit is configured to generate the acoustic signal to be outputted by the loudspeaker. The acoustic processing unit is further configured to modulate a predetermined acoustic signal by the at least one measurement parameter.

Abstract: A signal analysis method for analyzing a pulse modulated input signal is described. The signal analysis method includes: receiving the pulse modulated input signal, the input signal including a symbol sequence; recovering a clock signal from the input signal, the clock signal being associated with the input signal; sampling the input signal based on the clock signal, thereby obtaining a set of input signal samples, each of the input signal samples having a certain level being constant over time; determining at least two different levels of input signal samples being associated with different symbols of the symbol sequence; and determining at least one decision threshold based on the at least two different levels determined previously, the decision threshold being associated with a symbol transition of the symbol sequence. Further, a signal analysis apparatus is described.

Abstract: The present disclosure relates to an instrument for analyzing an input signal. The instrument comprises an input for receiving an input signal, a processing circuit or module for analyzing the input signal received, a display, such as a display module, for displaying information concerning the input signal analyzed, and a user input module for receiving instructions from a user. The instrument provides several functionalities, the several functionalities each being associated with at least one respective complexity. The instrument is set by the instructions of the user via the user input to analyze the input signal. The processing module evaluates a complexity of the instructions of the user.

Abstract: An approach for determining link transmission quality identifiers is provided. For this purpose, a two-step approach is applied. In a first step, quality indicators are obtained from a black-box device and related signal are obtained and recorded. Based on the recorded data, a model can be established or a neural network can be trained. The generated model or the trained network may be used for determining further quality indicators at any arbitrary point in time.

Abstract: A method for and apparatus processing a measurement signal of a dynamic physical quantity is provided which includes acquiring a measurement signal representing the dynamic physical quantity over time; comparing the acquired measurement signal with a predefined signal characteristic of the respective physical quantity or with a signal characteristic of another physical quantity being dependent from the respective physical quantity to provide a comparison result; and adjusting a waveform representing the acquired measurement signal based upon the comparison result. A digital oscilloscope is also provided.

Abstract: A signal analyzer for analyzing a signal comprises a frontend with at least two interleaved digitizers configured to digitize an input signal, thereby generating a digitized input signal. The signal analyzer also comprises a first interleave alignment filter established by a hardware interleave alignment filter that is configured to hardware-compensate non-ideal effects of the frontend in the digitized input signal in real-time, thereby generating a hardware-compensated, digitized input signal. Further, the signal analyzer comprises an acquisition memory configured to store the hardware-compensated, digitized input signal, thereby acquiring an acquired signal. Moreover, the signal analyzer comprises a second interleave alignment filter configured to fine-compensate further non-ideal effects of the frontend in a post-processing of the acquired signal. In addition, a method of analyzing a signal is described.