A Bayesian approach to blind source separation

This paper presents a Bayesian statistical approach to the blind source separation problem. The blind source separation model is described; the source distribution is discussed; other approaches such as Principal Components, Independent Components, and Factor Analysis are detailed; prior distributions are introduced to incorporate available prior knowledge; the posterior distribution for the model parameters (including the number of sources) is derived; and the parameter estimation procedure is outlined. Finally Bayesian blind source separation is applied in a simulated example and its advantages over the other methods are stated.