An Efficient Locally Adaptive Wavelet Denoising Method Based on Bayesian MAP Estimation

2006 ◽  
Author(s):  
Jianhua Hou ◽  
Chengyi Xiong
Keyword(s):  
Wavelet Denoising ◽  
Map Estimation ◽  
Denoising Method ◽  
Adaptive Wavelet ◽  
Locally Adaptive

scholarly journals Optimizing Signal De-Noising Algorithm for Acoustic Emission Leakage of Wavelet

2016 ◽  
Vol 16 (1) ◽  
pp. 116-125 ◽  
Author(s):  
Xin-Hua Wang ◽  
Yu-Lin Jiao ◽  
Yong-Chao Niu ◽  
Jie Yang
Keyword(s):  
High Pressure ◽  
Detection System ◽  
Minimum Mean Square Error ◽  
Weight Coefficient ◽  
Wavelet Denoising ◽  
Denoising Method ◽  
Adaptive Wavelet ◽  
Pressure Pipe ◽  
Optimal Linear ◽  
Mean Square Error Criterion

Abstract Traditional wavelet denoising method cannot eliminate complex high-pressure pipe signals effectively. In the updated wavelet adaptive algorithm, this thesis defines the constraints in order to reconstruct the signals accurately. According to the minimum mean square error criterion, the results predict the weight coefficient and get the optimal linear predictive value. Adopting the improved algorithm under the same condition, this thesis concluded that Db6 increased the complexity of wavelet algorithm by 50% by comparative experiments. It will be more conducive to the realization of hardware and the feasibility of real-time denoising. Dual adaptive wavelet denoising method improved SNR by 50%. This denoising method will play a key role in the detection rate of high-pressure pipe in the online leakage detection system.

The Study of Signal Denoising for Laser Cutting Based on Adaptive Wavelet Denoising

2012 ◽  
Vol 546-547 ◽  
pp. 686-690
Author(s):  
Hui Juan Hao ◽  
Ji Yong Xu ◽  
Juan Li
Keyword(s):  
Laser Cutting ◽  
Particle Swarm Optimization Algorithm ◽  
Wavelet Denoising ◽  
Quality Analysis ◽  
Signal Denoising ◽  
Threshold Method ◽  
Denoising Method ◽  
Swarm Optimization ◽  
Adaptive Wavelet ◽  
Soft Threshold

In order to reduce the noise of acquisition signal in laser cutting, an adaptive wavelet denoising method is proposed in this paper. Based on the analysis of the limitations of traditional threshold method, the particle swarm optimization algorithm is used to select the optimal threshold of wavelet. Compared with the commonly hard and soft threshold method, the experiment results show that the method used in this paper is relatively stable, and can reduce noise excellently. The method can provide more accurate signal for quality analysis in laser cutting .So the method can be used in noise denoising of pulse-induced acoustic sound.

Passive fetal monitoring by adaptive wavelet denoising method

2012 ◽  
Vol 42 (2) ◽  
pp. 171-179 ◽  
Author(s):  
Sergey Vaisman ◽  
Shimrit Yaniv Salem ◽  
Gershon Holcberg ◽  
Amir B. Geva
Keyword(s):  
Fetal Monitoring ◽  
Wavelet Denoising ◽  
Denoising Method ◽  
Adaptive Wavelet
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