@inproceedings{fe008ef979e64946b820c377084a89d7,
title = "An affine equivariant robust second-order BSS method",
abstract = "The interest in robust methods for blind source separation has increased recently. In this paper we shortly review what has been suggested so far for robustifying ICA and second order blind source separation. Furthermore do we suggest a new algorithm, eSAM-SOBI, which is an affine equivariant improvement of (already robust) SAM-SOBI. In a simulation study we illustrate the benefits of using eSAM-SOBI when compared to SOBI and SAM-SOBI. For uncontaminated time series SOBI and eSAM-SOBI perform equally well. However, SOBI suffers a lot when the data is contaminated by outliers, whereas robust eSAMSOBI does not. Due to the lack of affine equivariance of SAM-SOBI, eSAM-SOBI performs clearly better than it for both, contaminated and uncontaminated data.",
keywords = "ICA, Location and scatter functional, SOBI, Time series",
author = "Pauliina Ilmonen and Klaus Nordhausen and Hannu Oja and Fabian Theis",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2015 ; Conference date: 25-08-2015 Through 28-08-2015",
year = "2015",
doi = "10.1007/978-3-319-22482-4_38",
language = "English",
isbn = "9783319224817",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "328--335",
editor = "Zbynĕk Koldovsk{\'y} and Emmanuel Vincent and Arie Yeredor and Petr Tichavsk{\'y}",
booktitle = "Latent Variable Analysis and Signal Separation - 12th International Conference, LVA/ICA 2015, Proceedings",
}