Application of Bayesian Non-negative Source Separation to Mixture Analysis in Spectroscopy

In this paper we present an application of Bayesian non-negative source separation to the analysis of spectral mixtures obtained from the analysis of multicomponent substances. The processing aims are formalized as a non-negative source separation problem. The proposed Bayesian inference for the analysis is introduced and the main steps of the estimation algorithm are outlined. Some results obtained with simulated and experimental data are presented.