H. Saber

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This paper describes a hybrid blind source separation approach (HBS S A) for nonlinear mixing model (NL-BS S). The proposed hybrid scheme combines simply the kernel-feature spaces separation technique (KTDS EP) and the principle of the slow feature analysis (S FA). The nonlinear mixed data is mapped to high dimensional feature space using kernel-based(More)
This paper describes a hybrid blind source separation approach (HBSSA) for nonlinear mixing model (NL-BSS). The proposed hybrid scheme combines simply the kernel-feature spaces separation technique (KTDSEP) and the principle of the slow feature analysis (SFA). The nonlinear mixed data is mapped to high dimensional feature space using kernel-based method.(More)
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