Zusammenfassung
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 ...
Zusammenfassung
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 several several sources and it obtains the estimated coefficients of the unknown mixture matrix A and separates the unknown sources. Following an introduction, we present a brief abstract of previous work on geometric ICA by our two groups, the principles of the new method and a description of the algorithm followed by some speed enhancements. Finally, we illustrate with simulations of several source distributions how the algorithm performs.
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