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Robust regression of scattered data with adaptive spline-wavelets.

作者信息

Castaño Daniel, Kunoth Angela

机构信息

European Molecular Biology Laboratory, Heidelberg, Germany.

出版信息

IEEE Trans Image Process. 2006 Jun;15(6):1621-32. doi: 10.1109/tip.2006.871164.

DOI:10.1109/tip.2006.871164
PMID:16764286
Abstract

A coarse-to-fine data fitting algorithm for irregularly spaced data based on boundary-adapted adaptive tensor-product semi-orthogonal spline-wavelets has been proposed in Castaño and Kunoth, 2003. This method has been extended in Castaño and Kunoth, 2005 to include regularization in terms of Sobolev and Besov norms. In this paper, we develop within this least-squares approach some statistical robust estimators to handle outliers in the data. Our wavelet scheme yields a numerically fast and reliable way to detect outliers.

摘要

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