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Complex wavelet based envelope detection method was designed to extract the impulsive features contained in the signal.
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In this paper, an envelope detection method for the vibration signal with amplitude modulation is proposed.
The envelope detection method is employed to preprocess the measured vibration data before the FFT algorithm is used for vibration analysis.
As a continuation, this paper studies into several envelope detection methods, including Hilbert transform, spectral correlation, band-pass squared rectifier and short-time RMS.
This paper presents a functional observer based fault detection method.
The methods currently employed either have poor performance because the detection of the tag's response is based on envelope detection or are costly because they are based on software-defined radio.
We implemented the CNN based detection method in MATLAB 2016b (The MathWorks, Natick, MA) with MatConvNet56 1.0-beta23.
In this paper, a correlation based detection method is used.
We consider the envelope-based detection method over the standard energy-based detection method [45, 48 50] mainly considering its simplicity in hardware implementation and computation.
Time interval = 20 min. Organs were tracked automatically using signal intensity profiles of cell membranes based on a peak detection method.
The spectrum sensing performance at the CR node is then theoretically analyzed based on noisy envelope detection together with the time domain spectral occupancy statistics.
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