Design and performances of a mid-infrared CH4 detection device with novel three-channel-based LS-FTF self-adaptive denoising structure

2011 ◽  
Vol 155 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Wei-Lin Ye ◽  
Chuan-Tao Zheng ◽  
Xin Yu ◽  
Cong-Xin Zhao ◽  
Zhan-Wei Song ◽  
...  
Keyword(s):  
Mid Infrared ◽  
Adaptive Denoising ◽  
Self Adaptive

A four-channel-based mid-infrared methane sensor system using novel optical/electrical dual-domain self-adaptive denoising algorithm

2022 ◽  
Vol 149 ◽  
pp. 106797
Author(s):  
Fang Song ◽  
Chuantao Zheng ◽  
Shuo Yang ◽  
Kaiyuan Zheng ◽  
Weilin Ye ◽  
...  
Keyword(s):  
Sensor System ◽  
Mid Infrared ◽  
Methane Sensor ◽  
Dual Domain ◽  
Adaptive Denoising ◽  
Self Adaptive

Electrical-domain self-adaptive mid-infrared laser-based methane sensor system

2018 ◽  
Vol 26 (8) ◽  
pp. 1910-1916
Author(s):  
宋 芳 SONG Fang ◽  
杨 硕 YANG Shuo ◽  
余 迪 YU Di ◽  
周言文 ZHOU Yan-wen ◽  
郑传涛 ZHENG Chuan-tao ◽  
...  
Keyword(s):  
Infrared Laser ◽  
Sensor System ◽  
Mid Infrared ◽  
Methane Sensor ◽  
Self Adaptive

Data Processing with an Innovation Self-Adaptive Denoising Amalgamation Algorithm

2014 ◽  
Vol 1003 ◽  
pp. 254-259
Author(s):  
Jian Yu Hu ◽  
Shu Ming Hou ◽  
Yan Fei Liu
Keyword(s):  
State Function ◽  
Observation Data ◽  
Optimal Solutions ◽  
Process Noise ◽  
Noise Statistic ◽  
Observation Noise ◽  
Non Linear System ◽  
Noise Statistics ◽  
Adaptive Denoising ◽  
Self Adaptive

The process noise and observation noise of a system are easily disturbed. It’s hard to know its statistic character. This paper proposes an innovation self-adaptive fading UPF algorithm to solve this problem. In the new algorithm, self-adaptive gradually vanishing UKF is used as weightiness density function of particle filter. New observation data is used to modify the error caused by state function of system and noise statistic parameter in time. What’s more, the new algorithm avoids traditional particle filter’s defect that it always gets part optimal solutions. Experiment results indicate that this new algorithm has a higher accuracy and robustness for the changeable noise statistics and non-linear system.

A Self-Adaptive Denoising Algorithm Based on Genetic Algorithm for Photon-Counting Lidar Data

2021 ◽  
pp. 1-5
Author(s):  
Guo Zhang ◽  
Weiqi Lian ◽  
Shaoning Li ◽  
Hao Cui ◽  
Maoqiang Jing ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Photon Counting ◽  
Lidar Data ◽  
Adaptive Denoising ◽  
Self Adaptive

Research on Adaptive Denoising Method for Surface Roughness Measuring

2010 ◽  
Vol 139-141 ◽  
pp. 2117-2120
Author(s):  
Xiao Bin Pan ◽  
Xiao Jun Zhou ◽  
Zu Sheng You
Keyword(s):  
Surface Roughness ◽  
Adaptive Filtering ◽  
Least Square ◽  
Lms Algorithm ◽  
Denoising Method ◽  
Gaussian Filtering ◽  
Working Principle ◽  
Adaptive Gaussian Filtering ◽  
Adaptive Denoising ◽  
Self Adaptive

This paper analyses the method of denoising surface roughness profile signal using self-adaptive filtering technique.The working principle of self-adaptive denoising has been introduced.Method of combining of self-adaptive filter and least square error(LMS) algorithm has been designed.Results obtained from sin-wave with noise are validated using the LMS algorithm to eliminate noise.Comparison of caculating surface roughness mean line between self-adaptive Gaussian filtering meanline and ordinary Gaussian filtering meanline has been presented.From the simulation of self-adaptive denoising it is observed that the designed method can be used as a denoising method in the surface roughness measuring.

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