DocumentCode
2226857
Title
The Study of The Denoising and the Trend Extraction Method of Signal
Author
Anbing, Zhang ; Liu xinxia ; Liu Hui
Author_Institution
Hebei Univ. of Eng., Handan, China
fYear
2009
fDate
26-28 Dec. 2009
Firstpage
703
Lastpage
706
Abstract
Based on the capability of orthogonal wavelet transform in de-noise and trend extract function of EMD, a new noise filter and trend extraction model is built up. Then, simulated data is used to test the method. The following conclusions are drawn from these tests: (1) Orthogonal wavelet transform and EMD method can better mitigate the random errors which hide in periodic signal; (2) For signal with linear trend, Orthogonal wavelet transform filtering method is superior to EMD. (3) For signal with nonlinear trend, theoretic analysis and simulation results show that the new noise filter and trend extraction model is superior to EMD and to union simply wavelet and EMD method. This method greatly improves accuracy of the extracted deformation.
Keywords
feature extraction; filtering theory; signal denoising; wavelet transforms; EMD method; deformation extraction; noise filter; orthogonal wavelet transform; random errors; signal denoising; trend extraction method; Data mining; Filtering; Filters; Noise generators; Noise level; Noise reduction; Signal processing; Testing; Wavelet coefficients; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-4909-5
Type
conf
DOI
10.1109/ICISE.2009.1296
Filename
5455295
Link To Document