Title :
Combining SVD With wavelet transform in synthetic seismic signal denoising
Author :
Li, Ya-jun ; Yang, Bao-jun ; Li, Yue ; Zeng, Qian
Author_Institution :
Jilin Univ., Changchun
Abstract :
In order to gain effective signal from synthetic seismogram disturbed by random noise and strong surface wave, this paper, to start with, recovers surface wave events by the method of singular value decomposition (SVD). After eliminating surface wave from the synthetic seismogram, the methods of wavelet transform and the local SVD are used for suppressing partial random noise. A new method, introduced to determine the optimal slope of the surface wave, helps to extract surface wave better. Simulations have confirmed that it is effective to process the synthetic seismogram.
Keywords :
geophysical signal processing; seismology; signal denoising; signal synthesis; singular value decomposition; wavelet transforms; random noise suppression; singular value decomposition; surface wave event; synthetic seismic signal denoising; synthetic seismogram; wavelet transform; Educational institutions; Frequency; Notice of Violation; Pattern analysis; Pattern recognition; Signal denoising; Singular value decomposition; Surface waves; Wavelet analysis; Wavelet transforms; local SVD; random noise; seismogram; singular value decomposition (SVD); surface wave; wavelet transform;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
DOI :
10.1109/ICWAPR.2007.4421752