Clustering approach to square and non-square blind source separation

Recently, a number of heuristic techniques, mostly based on topographic maps, have been introduced in order to overcome (some) of the limitations of the blind source separation (BSS) algorithms that are rooted in the theory of independent component analysis. Here, we introduce a new heuristic that relies on the tendency of the mixture samples to cluster around the source directions in mixture space. We use linear mixtures of speech signals and consider BSS problems with not only square but also non-square mixing matrices (less mixtures than sources).