scholarly journals Signal-Processing Framework for Ultrasound Compressed Sensing Data: Envelope Detection and Spectral Analysis

2020 ◽  
Vol 10 (19) ◽  
pp. 6956
Author(s):  
Yisak Kim ◽  
Juyoung Park ◽  
Hyungsuk Kim

Acquisition times and storage requirements have become increasingly important in signal-processing applications, as the sizes of datasets have increased. Hence, compressed sensing (CS) has emerged as an alternative processing technique, as original signals can be reconstructed using fewer data samples collected at frequencies below the Nyquist sampling rate. However, further analysis of CS data in both time and frequency domains requires the reconstruction of the original form of the time-domain data, as traditional signal-processing techniques are designed for uncompressed data. In this paper, we propose a signal-processing framework that extracts spectral properties for frequency-domain analysis directly from under-sampled ultrasound CS data, using an appropriate basis matrix, and efficiently converts this into the envelope of a time-domain signal, avoiding full reconstruction. The technique generates more accurate results than the traditional framework in both time- and frequency-domain analyses, and is simpler and faster in execution than full reconstruction, without any loss of information. Hence, the proposed framework offers a new standard for signal processing using ultrasound CS data, especially for small and portable systems handling large datasets.

Author(s):  
Isabela M. Nobre ◽  
Julio L. Nicolini ◽  
Joaquim D. Garcia ◽  
Marbey Mosso

2012 ◽  
Vol 155-156 ◽  
pp. 470-473
Author(s):  
Shu Peng Wei

The ultrasonic nondestructive detection measurement techniques is so successful, it not only based on production and income measures of the wave, but also to the basis and the shrinkage of the waveform of get signal processing. Although the traditional time domain method can successfully sure small cracks, but you can't estimate the size of the crack, especially in the strong scattering noise to the influence of the after. Experimental results show that this algorithm not only has excellent performance, still can strong presence of noise in the signal processing, also can succeed estimate the size and location of the crack. In addition, this algorithm can be applied to ultrasonic nondestructive signal data compression.


2019 ◽  
Vol 8 (2S8) ◽  
pp. 1087-1091

Harmonic analysis of the power system signal is a proliferating research in the field of electronics technology. Whenever, we analyze odd and ever harmonics are present in the signal, imperative operation is needed to transform from the time domain to the frequency domain. Hence, all the researchers are utilizing the Fourier Transform technique is very effective for the analysis of odd and even harmonics in the frequency domain. In the past two decades, Wavelet Transform is a wonderful technique to analyze the harmonics both frequency and time domain as well. The analysis of harmonic and its probability distribution are most important for the purpose to predict the harmonic effects in the present situation. We treated all the harmonics and its corresponding frequency distribution are considered as a zero mean unit variance. The overlapping these distributions (small, medium, large) are analyzed with help of statistical data processing technique. It is one of the most important basic plots in the decision theory and it provides the constructive decision about the overlapping of a frequency distribution in power system signal. The curvature as a plot of sensitivity and specificity underlying the harmonics are present and not present distributive (Gaussian). The above determined values are lying in the interval probability [0, 1] and it is depends only the nature of the dataset. In this paper, we explained with help of MATLAB and level of understand the basic concept of ROC is demonstrated. The dataset is drawn from the example of odd and even harmonics are generated and the probability distribution as input to our MATLAB program.


2016 ◽  
Vol 78 (7-4) ◽  
Author(s):  
Priscilla Sim Chee Mei ◽  
Anita Ahmad

Atrial fibrillation (AF) has been widely stated as the most common arrhythmias (irregularities of heart rhythm) which could lead to severe heart problem such as stroke. Many studies have been conducted to understand and explain its mechanism by analyzing its signal, in either time domain or frequency domain. This paper aims to provide basic information on the AF by reviewing relevant papers. Overall, this paper will provide review on the underlying theory of AF, AF mechanism as well as the common relevant signal processing steps and analysis.


1993 ◽  
Vol 19 (3) ◽  
pp. 211-219 ◽  
Author(s):  
H. Rijsterborgh ◽  
F. Mastik ◽  
C.T. Lancée ◽  
P. Verdouw ◽  
J. Roelandt ◽  
...  

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