2010 | OriginalPaper | Buchkapitel
A General Approach for Robustification of ICA Algorithms
verfasst von : Matthew Anderson, Tülay Adalı
Erschienen in: Latent Variable Analysis and Signal Separation
Verlag: Springer Berlin Heidelberg
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This paper presents a general and robust approach to mitigating impact of outliers in independent component analysis applications. The approach detects and removes outlier samples from the dataset and has minimal impact on the overall performance when the dataset is free of outliers. It also has minimal computational burdens, is simply parameterized, and readily implemented. Significant gains in performance is shown for algorithms when outliers are present.