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 :
بازگشت