A method for processing a signal to extract a useful signal from a disturbed signal P1 if the disturbed signal P1 is formed as a sum of a sinusoidal component S1 and an additional component X1. The useful signal corresponds to one of these components. Values of the disturbed signal P1 at three successive times t1, t2 and t3 are determined. Values at the three times t1, t2 and t3 are determined of a signal P2 having a sinusoidal component Sa of the same amplitude as the sinusoidal component S1 and in phase quadrature with respect to the sinusoidal component S1. A value of the useful signal at time t3 based on the values of the disturbed signal P1 and the values of the signal P2 at the three successive times t1, t2 and t3 is calculated.

A method for processing a signal to extract a useful signal from a disturbed signal P1 if the disturbed signal P1 is formed as a sum of a sinusoidal component S1 and an additional component X1. The useful signal corresponds to one of these components. Values of the disturbed signal P1 at three successive times t1, t2 and t3 are determined. Values at the three times t1, t2 and t3 are determined of a signal P2 having a sinusoidal component Sa of the same amplitude as the sinusoidal component S1 and in phase quadrature with respect to the sinusoidal component S1. A value of the useful signal at time t3 based on the values of the disturbed signal P1 and the values of the signal P2 at the three successive times t1, t2 and t3 is calculated.

The present disclosure relates to an apparatus and method for motor imagery classification using electroencephalography (EEG), and more particularly, to an apparatus and method for motor imagery classification that extracts features in different domains included in EEG signals generated during motor imagery in real time and classifies a user's intentions using the features.

The present disclosure relates to an apparatus and method for motor imagery classification using electroencephalography (EEG), and more particularly, to an apparatus and method for motor imagery classification that extracts features in different domains included in EEG signals generated during motor imagery in real time and classifies a user's intentions using the features.

Embodiments of the invention include a resonant sensing system comprising driving circuitry to generate a drive signal during excitation time periods, a first switch coupled to the driving circuitry, and a sensing device coupled to the driving circuitry via the first switch during the excitation time periods. The sensing device includes beams to receive the drive signal during a first excitation time period that causes the beams to mechanically oscillate and generate a first induced electromotive force (emf) in response to the drive signal. The first switch decouples the sensing device and the driving circuitry during measurement time periods for measurement of the induced emf.

Embodiments of the invention include a resonant sensing system comprising driving circuitry to generate a drive signal during excitation time periods, a first switch coupled to the driving circuitry, and a sensing device coupled to the driving circuitry via the first switch during the excitation time periods. The sensing device includes beams to receive the drive signal during a first excitation time period that causes the beams to mechanically oscillate and generate a first induced electromotive force (emf) in response to the drive signal. The first switch decouples the sensing device and the driving circuitry during measurement time periods for measurement of the induced emf.

The present disclosure relates to a recloser control that detects islanding based on a continuous analysis of frequency and rate of change of frequency. For example, a recloser control may include protection circuitry that is communicatively coupled to a recloser. The recloser control may receive measurements of an electrical characteristic in an electric power delivery system. The recloser control may determine frequency (F) and a rate of change of frequency (ROCOF) based on the received measurements. The recloser control may detect islanding of a microgrid in the electric power delivery system based at least in part on F and ROCOF. The recloser control may send a signal to the recloser to trip the recloser based on the islanding of the microgrid.

The present disclosure relates to a recloser control that detects islanding based on a continuous analysis of frequency and rate of change of frequency. For example, a recloser control may include protection circuitry that is communicatively coupled to a recloser. The recloser control may receive measurements of an electrical characteristic in an electric power delivery system. The recloser control may determine frequency (F) and a rate of change of frequency (ROCOF) based on the received measurements. The recloser control may detect islanding of a microgrid in the electric power delivery system based at least in part on F and ROCOF. The recloser control may send a signal to the recloser to trip the recloser based on the islanding of the microgrid.

A test and measurement instrument, such as an oscilloscope, having a Nyquist frequency lower than an analog bandwidth, the test and measurement instrument having an input configured to receive a signal under test having a repeating pattern, a single analog-to-digital converter configured to receive the signal under test and sample the signal under test over a plurality of repeating patterns at a sample rate, and one or more processors configured to determine a frequency of the signal under test and reconstruct the signal under test based on the determined frequency of the signal, the pattern length of the signal under test, and/or the sample rate without a trigger.

A test and measurement instrument, such as an oscilloscope, having a Nyquist frequency lower than an analog bandwidth, the test and measurement instrument having an input configured to receive a signal under test having a repeating pattern, a single analog-to-digital converter configured to receive the signal under test and sample the signal under test over a plurality of repeating patterns at a sample rate, and one or more processors configured to determine a frequency of the signal under test and reconstruct the signal under test based on the determined frequency of the signal, the pattern length of the signal under test, and/or the sample rate without a trigger.