Quadrature Doppler Ultrasound Signal Denoising Based on Matching Pursuits with Different Time-Frequency Dictionaries

2007 ◽  
Author(s):  
Xiaotao Wang ◽  
Xingbo Wang
Keyword(s):  
Doppler Ultrasound ◽  
Signal Denoising ◽  
Time Frequency ◽  
Matching Pursuits ◽  
Ultrasound Signal

Doppler ultrasound signal denoising based on wavelet frames

2001 ◽  
Vol 48 (3) ◽  
pp. 709-716 ◽  
Author(s):  
Yu Zhang ◽  
Yuanyuan Wang ◽  
Weiqi Wang ◽  
Bin Liu
Keyword(s):  
Doppler Ultrasound ◽  
Signal Denoising ◽  
Wavelet Frames ◽  
Ultrasound Signal

Time-Frequency Analysis of the Blood Flow Doppler Ultrasound Signal

2001 ◽  
Vol 40 (Part 1, No. 5B) ◽  
pp. 3882-3887 ◽  
Author(s):  
Yasuaki Noguchi ◽  
Eiichi Kashiwagi ◽  
Kohtaro Watanabe ◽  
Fujihiko Matsumoto ◽  
Suguru Sugimoto
Keyword(s):  
Blood Flow ◽  
Doppler Ultrasound ◽  
Frequency Analysis ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Ultrasound Signal

scholarly journals Sirukumab and adalimumab reduce power Doppler ultrasound signal in patients with rheumatoid arthritis by 4 weeks in a phase III trial

2019 ◽  
Vol 78 (10) ◽  
pp. 1439-1441
Author(s):  
Kristen Sweet ◽  
Bidisha Dasgupta ◽  
Dick de Vries ◽  
Ian Gourley ◽  
Benjamin Hsu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Doppler Ultrasound ◽  
Power Doppler ◽  
Phase Iii ◽  
Power Doppler Ultrasound ◽  
Phase Iii Trial ◽  
Ultrasound Signal

Wavelet decomposition and nonlinear prediction of nonstationary vibration signals

2020 ◽  
Vol 51 (3) ◽  
pp. 52-59 ◽  
Author(s):  
Xiao-bin Fan ◽  
Bin Zhao ◽  
Bing-xu Fan
Keyword(s):  
Wavelet Decomposition ◽  
Wavelet Packet ◽  
Prediction Method ◽  
Vibration Signal ◽  
Signal Denoising ◽  
Maximum Lyapunov Exponent ◽  
Nonlinear Prediction ◽  
Local Method ◽  
Time Frequency ◽  
Nonstationary Vibration

In order to overcome the shortcomings (such as the time–frequency localization and the nonstationary signal analysis ability) of the Fourier transform, time–frequency analysis has been carried out by wavelet packet decomposition and reconstruction according to the actual nonstationary vibration signal from a large equipment located in a large Steel Corporation in this article. The effect of wavelet decomposition on signal denoising and the selection of high-frequency weight coefficients for each layer on signal denoising were analyzed. The nonlinear prediction of the chaotic time series was made by global method, local method, weighted first-order local method, and maximum Lyapunov exponent prediction method correspondingly. It was found the multi-step prediction method is better than other prediction methods.

Denoising Vibration Signals of Food Refrigerant Air Compressor Based on Wavelet Transform

2010 ◽  
Vol 439-440 ◽  
pp. 1037-1041 ◽  
Author(s):  
Yan Jue Gong ◽  
Zhao Fu ◽  
Hui Yu Xiang ◽  
Li Zhang ◽  
Chun Ling Meng
Keyword(s):  
Wavelet Transform ◽  
Frequency Characteristic ◽  
Vibration Signal ◽  
Wavelet Denoising ◽  
Signal Denoising ◽  
Denoising Method ◽  
Vibration Signals ◽  
Air Compressor ◽  
Time Frequency ◽  
Soft Threshold

On the basis of wavelet denoising and its better time-frequency characteristic, this paper presents an effective vibration signal denoising method for food refrigerant air compressor. The solution of eliminating strong noise is investigated with the combination of soft threshold and exponential lipschitza. The good denoising results show that the presented method is effective for improving the signal noise ratio and builds the good foundation for further extraction of the vibration signals.

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