@misc{cogprints7056,
           month = {October},
           title = {An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation},
          author = {Dr. Henning Sprekeler and Tiziano Zito and Dr. Laurenz Wiskott},
            year = {2010},
        keywords = {slow feature analysis, nonlinear blind source separation, independent component analysis},
             url = {http://cogprints.org/7056/},
        abstract = {We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of statistically independent sources from arbitrary nonlinear instantaneous mixtures. Simulations show that it is able to invert a complicated nonlinear mixture of two audio signals with a reliability of more than \$90\${$\backslash$}\%. The algorithm is based on a  mathematical analysis of slow feature analysis for the case of input data that are generated from statistically independent sources.}
}

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