DocumentCode
3347751
Title
A Bayesian method for positive source separation
Author
Moussaoui, Said ; Brie, David ; Caspary, Olivier ; Mohammad-Djafari, Ali
Author_Institution
CRAN CNRS UMR 7039, Nancy, France
Volume
5
fYear
2004
fDate
17-21 May 2004
Abstract
The paper considers the problem of source separation in the particular case where both the sources and the mixing coefficients are positive. The proposed method addresses the problem in a Bayesian framework. We assume a gamma distribution for the spectra and the mixing coefficients. This prior distribution enforces the non-negativity. This leads to an original method for positive source separation. A simulation example is presented to illustrate the effectiveness of the method.
Keywords
Bayes methods; gamma distribution; source separation; spectral analysis; spectrochemical analysis; Bayes method; Bayesian framework; analytical chemistry; gamma distribution; mixing coefficients; positive source separation; qualitative analysis; quantitative analysis; sample analysis; spectral data; Bayesian methods; Chemistry; Constraint optimization; Data analysis; Frequency; Independent component analysis; Iterative algorithms; Source separation; Spectral analysis; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8484-9
Type
conf
DOI
10.1109/ICASSP.2004.1327153
Filename
1327153
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