@inbook{59a7624cce5640b8b80f4ffe524a42e5,
title = "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)).",
author = "Meinecke, {Frank C.} and Stefan Harmeling and M{\"u}ller, {Klaus Robert}",
year = "2004",
doi = "10.1007/978-3-540-30110-3_28",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "217--224",
editor = "Puntonet, {Carlos G.} and Alberto Prieto",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}