DocumentCode
2207087
Title
Source separation of baseband signals in Post-Nonlinear mixtures
Author
Duarte, L.T. ; Jutten, C. ; Rivet, B. ; Suyama, R. ; Attux, R. ; Romano, J. M T
Author_Institution
GIPSA-Lab., Inst. Polytech. de Grenoble, St. Martin d´´Heres, France
fYear
2009
fDate
1-4 Sept. 2009
Firstpage
1
Lastpage
6
Abstract
Usually, source separation in Post-Nonlinear (PNL) models is achieved via one-stage methods, i.e. the two parts (linear and nonlinear) of a PNL model are dealt with at the same time. However, recent works have shown that the development of two-stage techniques may simplify the problem. Indeed, if the nonlinear stage can be compensated separately, then, in a second moment, one can make use of the well-established source separation algorithms for the linear case. Motivated by that, we propose in this work a novel two-stage PNL method relying on the assumption that the sources are bandlimited signals. In the development of our method, special care is taken in order to make it as robust as possible to noise. Simulation results attest the effectiveness of the proposal.
Keywords
source separation; baseband signal source separation algorithm; post-nonlinear mixture model; Acoustic noise; Baseband; Data mining; Entropy; Gaussian processes; Independent component analysis; Mutual information; Noise robustness; Signal processing; Source separation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location
Grenoble
Print_ISBN
978-1-4244-4947-7
Electronic_ISBN
978-1-4244-4948-4
Type
conf
DOI
10.1109/MLSP.2009.5306214
Filename
5306214
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