A new signal denoising method based on wavelet threshold algorithm

2016 ◽  
Author(s):  
Liming Chen ◽  
Bin Xie
Keyword(s):  
Signal Denoising ◽  
Denoising Method ◽  
Threshold Algorithm

Analysis of ECG signal denoising method based on S-transform

IRBM ◽  
2013 ◽  
Vol 34 (6) ◽  
pp. 362-370 ◽  
Author(s):  
M.K. Das ◽  
S. Ari
Keyword(s):  
Signal Denoising ◽  
Ecg Signal ◽  
Denoising Method ◽  
S Transform

Partial discharge signal denoising method based on frequency spectrum clustering and local mean decomposition

2020 ◽  
Vol 14 (10) ◽  
pp. 853-861
Author(s):  
Shanjun Li ◽  
Sashuang Sun ◽  
Qin Shu ◽  
Minwei Chen ◽  
Dakun Zhang ◽  
...  
Keyword(s):  
Frequency Spectrum ◽  
Partial Discharge ◽  
Signal Denoising ◽  
Denoising Method ◽  
Local Mean Decomposition ◽  
Local Mean

Improved Wavelet Threshold Denoising Method

2014 ◽  
Vol 602-605 ◽  
pp. 3177-3180
Author(s):  
Wei Ping Cui ◽  
Li Juan Du
Keyword(s):  
Traditional Method ◽  
Wavelet Denoising ◽  
Threshold Function ◽  
Signal Denoising ◽  
Improved Method ◽  
Denoising Method ◽  
Comparison And Analysis ◽  
Selection Of

In this paper, through comparison and analysis of various wavelet denoising methods, a new threshold function is constructed, and the selection of threshold is improved. Signal denoising simulation is made by the software MATLAB, the results show that the improved method is superior to the traditional method, and obtain a better denoising effect.

scholarly journals An Integrated Denoising Method for Sensor Mixed Noises Based on Wavelet Packet Transform and Energy-Correlation Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Chao Tan ◽  
Yanping Wang ◽  
Xin Zhou ◽  
Zhongbin Wang ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Processing Method ◽  
Signal Denoising ◽  
Current Signal ◽  
Energy Correlation ◽  
Denoising Method ◽  
Impact Noise ◽  
Key Technologies

In order to solve the problem of industrial sensor signal denoising, an integrated denoising method for sensor mixed noises based on wavelet packet transform and energy-correlation analysis is proposed. The architecture of proposed method is designed and the key technologies, such as wavelet packet transformation, energy-correlation analysis, and processing method of wavelet packet coefficients based on energy-correlation analysis, are presented. Finally, a simulation example for a specific signal and an application of shearer cutting current signal, which mainly contain white Gaussian noise and impact noise, are carried out, and the simulation and application results show that the proposed method is effective and is outperforming others.

Research on improved FAWT signal denoising method in evaluation of firefighter training efficacy based on sEMG

2022 ◽  
Vol 72 ◽  
pp. 103336
Author(s):  
Yang Li ◽  
Ke Bai ◽  
Hao Wang ◽  
Simeng Chen ◽  
Xuejun Liu ◽  
...  
Keyword(s):  
Signal Denoising ◽  
Denoising Method

HD-sEMG Signal Denoising Method for Improved Classification Performance in Transhumeral Amputees Pros thesis Control

2021 ◽  
Author(s):  
Mojisola Grace Asogbon ◽  
Oluwarotimi Williams Samuel ◽  
Esugbe Ejay ◽  
Yazan Ali Jarrah ◽  
Shixiong Chen ◽  
...  
Keyword(s):  
Classification Performance ◽  
Signal Denoising ◽  
Semg Signal ◽  
Denoising Method

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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