Title :
A MAP solution to blind source separation
Author :
Igual, Jorge ; Vergara, Luis
Author_Institution :
Dept. of Comunicaciones, Univ. Politecnica de Valencia, Spain
Abstract :
In blind source separation nothing is supposed about the mixing matrix. Nevertheless, sometimes we have a previous knowledge about some of the elements aij, not about the structure of the mixing matrix. We model this a priori knowledge with a probability density function, then a maximum a posteriori (MAP) or Bayes approach to the problem is proposed in this paper
Keywords :
Bayes methods; matrix algebra; maximum likelihood estimation; probability; signal processing; Bayes approach; MAP estimation; a priori knowledge; blind source separation; maximum a posteriori estimation; mixing matrix; probability density function; Array signal processing; Bibliographies; Blind source separation; Contracts; Decorrelation; Density functional theory; Probability density function; Source separation;
Conference_Titel :
Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Caesarea
Print_ISBN :
0-7695-0140-0
DOI :
10.1109/HOST.1999.778705
