ICA 2007

ICA 2007
7th International Conference on
Independent Component Analysis
and Signal Separation

London, UK        9 - 12 September 2007

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Paper No: 38

Probabilistic Geometric Approach to Blind Separation of Time-Varying Mixtures

Author(s): Ran Kaftory, Yehoshua Zeevi

Abstract

We consider the problem of blindly separating time-varying instantaneous mixtures. It is assumed that the arbitrary dependency of the mixing coefficient on time, is known up to a finite number of parameters. Using sparse (or sparsified) sources, we geometrically identify samples of the curves representing the parametric model. The parameters are found using a probabilistic approach of estimating the maximum likelihood of a curve, given the data. After identifying the model parameters the mixing system is inverted to estimate the sources. The new approach to blind separation is demonstrated using both synthetic and real data.

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