Independent component analysis for mixture densities
نویسندگان
چکیده
Independent component analysis (ICA), formulated as a density estimation problem, is extended to a mixture density model. A number of ICA blocks, associated to implicit equivalent classes, are updated in turn on the basis of the estimated density they represent. The approach is equivalent to the EM algorithm and allows an easy non linear extension of all the current ICA algorithms. We also show a preliminary test on bi-dimensional synthetic data drawn from a mixture model.
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