Title :
An application of the learning theory to wavelet based signal denoising
Author :
M. Stankovic;S. Stankovic
Author_Institution :
IRITEL, Belgrade, Serbia
fDate :
6/26/1905 12:00:00 AM
Abstract :
In this paper the statistical learning theory is applied to signal denoising using wavelets. The methodology is based on the estimation of the functional relationship between the Vapnik-Chervonenkis (VC) dimension and approximation complexity. Experimental results confirm the basic assumptions.
Keywords :
"Signal denoising","Least squares approximation","Function approximation","Noise reduction","Discrete wavelet transforms","Digital filters","Filtering theory","Fourier transforms","Signal processing","Virtual colonoscopy"
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2004. NEUREL 2004. 2004 7th Seminar on
Print_ISBN :
0-7803-8547-0
DOI :
10.1109/NEUREL.2004.1416588
