Blind Source Separation in Nonlinear Mixture for Colored Sources Using Signal Derivatives

Abstract : While Blind Source Separation (BSS) for linear mixtures has been well studied, the problem for nonlinear mixtures is still thought not to have a general solution. Each of the techniques proposed for solving BSS in nonlinear mixtures works mainly on specific models and cannot be generalized for many other realistic applications. Our approach in this paper is quite different and targets the general form of the problem. In this advance, we transform the nonlinear problem to a time-variant linear mixtures of the source derivatives. The proposed algorithm is based on separating the derivatives of the sources by a modified novel technique that has been developed and specialized for the problem, which is followed by an integral operator for reconstructing the sources. Our simulations show that this method separates the nonlinearly mixed sources with outstanding performance; however , there are still a few more steps to be taken to get to a comprehensive solution which are mentioned in the discussion.
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Submitted on : Monday, November 9, 2015 - 4:10:51 PM
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Bahram Ehsandoust, Masoud Babaie-Zadeh, Christian Jutten. Blind Source Separation in Nonlinear Mixture for Colored Sources Using Signal Derivatives. 12th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2015), Technical University of Libere, Aug 2015, Liberec, Czech Republic. pp 193-200, ⟨10.1007/978-3-319-22482-4_22⟩. ⟨hal-01226466⟩



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