DocumentCode
690415
Title
Threshold of Denoising Weak Electrical Signals in Plants from Daubechies Wavelet Transform
Author
Changcheng Li ; Laiwu Yin ; Dong Chen ; Xiaohong Tang
Author_Institution
Coll. of Electr. & Inf. Eng., Jilin Agric. Sci. & Technol. Coll., Jilin, China
fYear
2013
fDate
14-15 Dec. 2013
Firstpage
600
Lastpage
603
Abstract
In order to find the solution to the problems in collection and identification of the weak electrical signals in the physical environment, this paper, based on the analysis of the relevant principles, presents a denoising method using multilevel threshold based on the detailed coefficients of Daubechies wavelet transform through a deduction process of the method. This method uses the analysis of the minimum frequency components of signals to determine the maximum decomposition levels with the ability of extracting and processing the plant weak electrical signals. The simulation experiments show the method is effective in denoising, especially for the restoration of the weak electrical signals with high noise background, and it can be used in extracting and processing the weak electrical signals and is an effective method of detecting the signals.
Keywords
agriculture; bioelectric phenomena; signal denoising; signal detection; wavelet transforms; Daubechies wavelet transform; agriculture engineering; decomposition levels; minimum signal frequency components analysis; multilevel threshold; plants; weak electrical signal denoising; weak electrical signal detection; weak electrical signal extraction; weak electrical signal processing; Noise reduction; Signal to noise ratio; Wavelet analysis; Wavelet coefficients; Daubechies wavelet transform; denoising; weak electrical signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Sciences and Applications (CSA), 2013 International Conference on
Conference_Location
Wuhan
Type
conf
DOI
10.1109/CSA.2013.145
Filename
6835672
Link To Document