Title :
Wavelet denoising for highly noisy source separation
Author :
Paraschiv-Ionescu, A. ; Jutten, C. ; Aminian, K. ; Najafi, B. ; Robert, Ph.
Author_Institution :
Swiss Fed. Inst. of Technol., Lausanne, Switzerland
fDate :
6/24/1905 12:00:00 AM
Abstract :
The aim of this paper is to demonstrate that wavelet denoising processing is extremely attractive for efficient source separation of strong noisy mixtures. Systematic numerical simulations using source separation algorithms after wavelet denoising are used to provide quantitative evaluations of the efficiency of the method. The cases of correlated Gaussian and non-Gaussian noise are investigated, which open the way to various practical applications.
Keywords :
Gaussian noise; interference suppression; signal processing; wavelet transforms; ICA; blind source separation; correlated Gaussian noise; correlated nonGaussian noise; independent component analysis; strong noisy mixtures; wavelet denoising; Additive noise; Additive white noise; Biomedical measurements; Discrete wavelet transforms; Gaussian noise; Independent component analysis; Noise measurement; Noise reduction; Source separation; Working environment noise;
Conference_Titel :
Circuits and Systems, 2002. ISCAS 2002. IEEE International Symposium on
Print_ISBN :
0-7803-7448-7
DOI :
10.1109/ISCAS.2002.1009812
