Robust ICA for Super-Gaussian Sources

Meinecke, F; Harmeling, S; Müller, K-R

doi:10.1007/b100528

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Robust ICA for Super-Gaussian Sources

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https://link.springer.com/content/pdf/10.1007%2F978-3-540-30110-3_28.pdf
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Meinecke, F., Harmeling, S., & Müller, K.-R. (2004). Robust ICA for Super-Gaussian Sources. In C. Puntonet, & A. Prieto (Eds.), Independent Component Analysis and Blind Signal Separation: Fifth International Conference, ICA 2004, Granada, Spain, September 22-24, 2004 (pp. 217-224). Berlin, Germany: Springer.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D7A9-1

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 over-complete ICA (i.e. more source signals than observed signals (mixtures)).