Wind Lidar signal denoising method based onSingular Value Decomposition and Variational ModeDecomposition

2021 ◽  
Author(s):  
DAI HUIXING ◽  
Chunqing Gao ◽  
Zhifeng Lin ◽  
Kaixin Wang ◽  
ZHANG xu
Keyword(s):  
Signal Denoising ◽  
Lidar Signal ◽  
Denoising Method ◽  
Wind Lidar ◽  
Value Decomposition

Three-Dimensional Imaging Lidar Signal Denoising Method Based on Empirical Mode Decomposition

2011 ◽  
Vol 31 (12) ◽  
pp. 1211004
Author(s):  
焦宏伟 Jiao Hongwei ◽  
秦石乔 Qin Shiqiao ◽  
王省书 Wang Xingshu ◽  
胡春生 Hu Chunsheng ◽  
吴伟 Wu Wei
Keyword(s):  
Empirical Mode Decomposition ◽  
Three Dimensional ◽  
Signal Denoising ◽  
Lidar Signal ◽  
Denoising Method ◽  
Three Dimensional Imaging ◽  
Mode Decomposition

scholarly journals The Application of EMD-CIIT Lidar Signal Denoising Method in Aerosol Detection

2015 ◽  
Vol 102 ◽  
pp. 1233-1237 ◽  
Author(s):  
Pengfei Tian ◽  
Lei Zhang ◽  
Xianjie Cao ◽  
Nana Yi
Keyword(s):  
Signal Denoising ◽  
Lidar Signal ◽  
Denoising Method

scholarly journals A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1403
Author(s):  
Minghuan Hu ◽  
Jiandong Mao ◽  
Juan Li ◽  
Qiang Wang ◽  
Yi Zhang
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Mie Scattering ◽  
Signal Denoising ◽  
Lidar Signal ◽  
Measuring Process ◽  
Denoising Method ◽  
Lidar Return ◽  
Deep Learning Neural Network ◽  
Better Than

The lidar is susceptible to the dark current of the detector and the background light during the measuring process, which results in a significant amount of noise in the lidar return signal. To reduce noise, a novel denoising method based on the convolutional autoencoding deep-learning neural network is proposed. After the convolutional neural network was constructed to learn the deep features of lidar signal, the signal details were reconstructed by decoding part to obtain the denoised signal. To verify the feasibility of the proposed method, both the simulated signals and the actually measured signals by Mie-scattering lidar were denoised. Some comparisons with the wavelet threshold denoising method and the variational modal decomposition denoising method were performed. The results show the denoising effect of the proposed method was significantly better than the other two methods. The proposed method can eliminate complex noise in the lidar signal while retaining the complete details of the signal.

scholarly journals An Image Denoising Method with Enhancement of the Directional Features Based on Wavelet and SVD Transforms

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Min Wang ◽  
Zhen Li ◽  
Xiangjun Duan ◽  
Wei Li
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Denoising ◽  
High Frequency ◽  
Low Frequency ◽  
Singular Value ◽  
Denoising Method ◽  
Diagonal Part ◽  
Value Decomposition ◽  
Image Part

This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.

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.

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