A measurement device is described that comprises a measurement unit configured to perform measurements on an electric signal of a device under test while applying at least one measurement parameter for performing the measurements. The measurement device has an integrated direct current source configured to power the device under test. The measurement device also comprises a monitoring unit configured to monitor at least one monitoring parameter of the direct current source. The measurement device has a control unit configured to control the measurement parameter. Further, a method for measuring a device under test is described.

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.

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.

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.

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.

A direct current (DC) power rail probe includes a single-ended probe tip, and a two-path circuit having an input coupled to the single-ended probe tip and an output configured for connection to measurement equipment such as an oscilloscope. The two-path circuit includes an alternating current (AC) path in parallel with a feed-forward (FF) path, the AC path including a capacitive element, and the FF path including a series connection of at least one resistive element and an amplifier. The probe tip and two-path circuit are selectively operable in a non-attenuating mode and an attenuating mode.

A battery charger and method is disclosed for detecting when a battery has a low state of health while simultaneously charging or maintaining the battery. A battery charger includes a processor; a non-transitory memory device; a power management device to receive an input power and to output a charging current; a pair of electrical conductors to electrically couple with a battery, and a display electrically coupled to the processor. The display being configured to indicate a bad battery indicator when the battery has a low state of health and whether the battery is good to start.

An oscilloscope includes a time domain input, a logic domain input, and a frequency domain input. The time domain input provides a time domain input signal in a time domain as a first input signal. The logic domain input provides logic level input as a second input signal. The logic level input includes logic levels over time. The frequency domain input provides a third input signal through frequency downconversion.

Embodiments of the invention include methods and instruments for performing combinatorial mask triggering. One or more mask triggers can be configured. Combinatorial mask triggering logic can make various determinations about the relationship between a digitized signal and the one or more mask triggers. The various determinations about the relationship can include considerations of both space and time. When the combinatorial trigger criteria have been satisfied, a trigger signal is generated, and the digital data associated with an incoming signal is stored to memory. The combinatorial mask triggering logic can operate on signals in the frequency domain, the time domain, or both.

A method, apparatus, and energy metering system obtains mains samples of a mains power line signal, performs non-white noise (NWN) filtering of the mains power line signal, obtains adjustable clock source samples of an adjustable clock signal of an adjustable clock oscillator, determines a difference based on the mains samples and the adjustable clock source samples, adjusts an adjustable clock source frequency of the adjustable clock oscillator based on the difference, and applies the adjustable clock source frequency to an analog to digital converter (ADC) to determine a conversion rate of the ADC.