Robust ICA for Super-Gaussian Sources

Abstract. Most ICA algorithms are sensitive to outliers. Instead of robustifying existing algorithms by outlier rejection techniques, we show how a simple outlier index can be used directly to solve the ICA problem for super-Gaussian source signals. This ICA method is outlier-robust by construction and can be used for standard ICA as well as for overcomplete ICA (i.e. more source signals than observed signals (mixtures)).

• Type: Conference
• Year: 2004
• Where: ICA
• Authors: Frank C. Meinecke, Stefan Harmeling, Klaus-Robert Müller
• Keywords: ICA 2004, ICA Problem, Most ICA Algorithms, Source Signals