SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Separation of Polynomial Post Non-Linear Mixtures of Discrete Sources

Author(s)

Boaz Lachover	Tel-Aviv University
Arie Yeredor	Tel-Aviv University

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Abstract

We consider the problem of blind estimation of the parameters of noisy non-linear mixtures of sources with unknown discrete alphabets. The nonlinear mixtures are modeled using the ``post non-linear" model, in which the source signal undergo a linear mixture first, and then each mixed signal undergoes an unknown nonlinear transformation. The individual nonlinear transformations are modeled in this paper as second-order polynomials, whose parameters are unknown. Using the Estimate-Maximize algorithm, we derive estimators for all the unknown parameters. We also computed the Cram\'{e}r-Rao Lower Bound for the estimation, to which the obtained mean squared estimation error is empirically compared.