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@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.} }