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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
Print_ISBN :
0-7803-8484-9
DOI :
10.1109/ICASSP.2004.1327153