Histogram Based Blind Identification and Source Separation from Linear Instantaneous Mixtures

Authors:
Konstantinos I. Diamantaras;Theophilos Papadimitriou
Affiliations:
Department of Informatics, TEI of Thessaloniki, Sindos, Greece 57400;Department of Int. Economic Relat. and Devel., Democritus University of Thrace, Komotini, Greece 69100
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

Citing 3
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Abstract

The paper presents a new geometric method for the blind identification of linear instantaneous MIMO systems driven by multi-level inputs. The number of outputs may be greater than, equal to, or even less than the number of sources. The sources are then extracted using the identified system parameters. Our approach is based on the fact that the distribution of the distances between the cluster centers of the observed data cloud reveals the mixing vectors in a simple way. In the noiseless case the method is deterministic, non-iterative and fast: it suffices to calculate the histogram of these distances. In the noisy case, the core algorithm must be combined with efficient clustering methods in order to yield satisfactory results for various SNR levels.