A MAP solution to blind source separation
Jorge Igual, Luis Vergara · 2003
In blind source separation nothing is supposed about the mixing matrix. Nevertheless, sometimes we have a previous knowledge about some of the elements a/sub ij/, 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.