Separation of sources based on the partitioning of the space of observations

Abstract

The techniques of Blind Separation of Sources (BSS) are used in many Signal Processing applications in which the data sampled by sensors are a mixture of signals from different sources, and the goal is to obtain an estimation of the sources from the mixtures. This work shows a new method for blind separation of sources, based on geometrical considerations concerning the observation space. This new method is applied to a mixture of two sources and it obtains the coefficients of the unknown mixture matrix A and separates the unknown sources, So. Following an introduction, we present a brief abstract of previous work by other authors, the principles of the method and a description of the algorithm, together with some simulations. © Springer-Verlag Berlin Heidelberg 2001.