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 :
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