Patent classifications
G01R13/34
Continuous-time sampler circuits
A continuous-time sampler has series-connected delay lines with intermediate output taps between the delay lines. Signal from an output tap can be buffered by an optional voltage buffer for performance. A corresponding controlled switch is provided with each output tap to connect the output tap to an output of the continuous-time sampler. The delay lines store a continuous-time input signal waveform within the propagation delays. Controlling the switches corresponding to the output taps with pulses that match the propagation delays can yield a same input signal value at the output. The continuous-time sampler effectively holds or provides the input signal value at the output for further processing without requiring switched-capacitor circuits that sample the input signal value onto some capacitor. In some cases, the continuous-time sampler can be a recursively-connected delay line. The continuous-time sampler can be used as the front end sampler in a variety of analog-to-digital converters.
Continuous-time sampler circuits
A continuous-time sampler has series-connected delay lines with intermediate output taps between the delay lines. Signal from an output tap can be buffered by an optional voltage buffer for performance. A corresponding controlled switch is provided with each output tap to connect the output tap to an output of the continuous-time sampler. The delay lines store a continuous-time input signal waveform within the propagation delays. Controlling the switches corresponding to the output taps with pulses that match the propagation delays can yield a same input signal value at the output. The continuous-time sampler effectively holds or provides the input signal value at the output for further processing without requiring switched-capacitor circuits that sample the input signal value onto some capacitor. In some cases, the continuous-time sampler can be a recursively-connected delay line. The continuous-time sampler can be used as the front end sampler in a variety of analog-to-digital converters.
DISPLAY DATA GENERATION DEVICE, DISPLAY DATA GENERATION METHOD, AND PROGRAM
A display data generation device (10) includes: an acquisition unit (11) to acquire an input signal; a waveform generation module (161) (i) to extract, from waveform patterns predetermined as normal waveform patterns, a waveform pattern having the highest degree of similarity to the input signal for each interval of the input signal by using as the degree of similarity a degree to which waveforms are similar to each other and (ii) to generate a comparison waveform based on the waveform pattern extracted for each interval; and a data generation module (162) to generate and outputting display data for displaying a waveform of the input signal and the comparison waveform.
PATTERN ACQUISITIONS IN EQUIVALENT TIME SAMPLING SYSTEMS
An equivalent-time sampling test and measurement instrument for acquiring a repeating pattern signal under test at or near a maximum sampling speed of the test and measurement instrument. The test and measurement instrument includes a first input configured to receive repeating pattern information about a signal under test, a second input configured to receive the signal under test, one or more processors configured to determine an optimized trigger holdoff period that is set based on a minimum trigger holdoff period of a test and measurement instrument, and an acquisition unit configured to acquire a portion of the signal under test every optimized trigger holdoff period.
WAVEFORM SEGMENTATION DEVICE AND WAVEFORM SEGMENTATION METHOD
A waveform segmentation device has a state level estimation unit that estimates a state level of input waveform data, and a segmentation identification unit that segments the waveform data at a plurality of segmentation points based on the state level estimated by the state level estimation unit. The segmentation identification unit may identify the plurality of segmentation points such that a feature value of the waveform data is included between two adjacent segmentation points among the segmentation points.
Measurement apparatus and measurement method
An automated zooming of a signal waveform by a measurement device is provided. Vertical parameters of a zoom window for zooming a signal waveform are automatically determined. For this purpose, an acquired measurement signal is tracked and the parameters of the zoom window are set based on the tracking of the measurement signal.
Measurement apparatus and measurement method
An automated zooming of a signal waveform by a measurement device is provided. Vertical parameters of a zoom window for zooming a signal waveform are automatically determined. For this purpose, an acquired measurement signal is tracked and the parameters of the zoom window are set based on the tracking of the measurement signal.
Method and apparatus providing a trained signal classification neural network
A method for providing a training data set used for training a signal classification neural network, the method comprising the steps of: generating at least one first virtual waveform primitive comprising a predetermined signal level and at least one second virtual waveform primitive comprising a signal edge; forming the training data set comprising a predetermined number of generated virtual waveform primitives including first virtual waveform primitives and second virtual waveform primitives, wherein each virtual waveform primitive comprises a sequence of time and amplitude discrete values and using the training data set for training the signal classification neural network.
Method and apparatus providing a trained signal classification neural network
A method for providing a training data set used for training a signal classification neural network, the method comprising the steps of: generating at least one first virtual waveform primitive comprising a predetermined signal level and at least one second virtual waveform primitive comprising a signal edge; forming the training data set comprising a predetermined number of generated virtual waveform primitives including first virtual waveform primitives and second virtual waveform primitives, wherein each virtual waveform primitive comprises a sequence of time and amplitude discrete values and using the training data set for training the signal classification neural network.
Coherent Sampling
To realize sampling (signal measurement) and analysis of a signal to be measured easily at low cost by capturing optical phase fluctuation even when low-speed sampling is carried out. This sampling method includes: a step for acquiring main sampling points at a repetition period equal to or less than a half of the band frequency of a signal to be measured; a step for acquiring sub-sampling points by executing sampling separately from that executed for the main sampling points; a step for acquiring an amplitude difference, a phase difference, and a frequency difference between the signal to be measured at each of the sub-sampling points and a reference signal; a step for acquiring a time difference, an amplitude difference (A), a phase difference (), and a frequency difference (f) between each of the main sampling points and each of the sub-sampling points; and a step for acquiring the amplitude fluctuation, the phase fluctuation, and the frequency fluctuation of the signal to be measured by using the time difference (t), the amplitude difference (A), the phase difference (), and the frequency difference (f) between each of the main sampling points and each of the sub-sampling points.