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Robust ICA for Super-Gaussian Sources (2004)
| Content Provider | CiteSeerX |
|---|---|
| Author | Meinecke, Frank C. Müller, Klaus-Robert Harmeling, Stefan |
| Description | Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2004 |
| Abstract | 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)). 1 |
| File Format | |
| Publisher Date | 2004-01-01 |
| Access Restriction | Open |
| Subject Keyword | Ica Problem Super-gaussian Source Signal Overcomplete Ica Standard Ica Robust Ica Super-gaussian Source Ica Method Rejection Technique Ica Algorithm |
| Content Type | Text |
| Resource Type | Conference Proceedings Article |
