Abstract
The problem of finding the centers and scattering matrices for a finite set of points containing outliers in a multidimensional space is considered. A new approach is considered in which instead of the arithmetic mean, differentiable mean values are used that are insensitive to outliers. An iterative reweighting scheme for searching for centers and corresponding scattering matrices for the Mahalanobis distance is considered. The examples presented in the article show the robustness property of the proposed method and algorithm with respect to a large number of outliers.
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