Separation of Sources Based on the Partitioning of the Space of Observations

Authors:
Manuel Rodríguez-Álvarez;Carlos García Puntonet;Ignacio Rojas
Affiliations:
-;-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Year:
2001

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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.