Large scale least squares scattered data fitting

Authors:
V. Pereyra;G. Scherer
Affiliations:
Weidlinger Associates, 4410 El Camino Real #110, 94022 Los Altos, CA;Weidlinger Associates, 4410 El Camino Real #110, 94022 Los Altos, CA
Venue:
Applied Numerical Mathematics
Year:
2003

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Abstract

The least squares approximation by tensor products of B-splines of large sets of scattered data is considered. This ill-conditioned or even singular problem requires special techniques, some of which are described in this paper. The performance of a Block Truncated Singular Value Decomposition (BTSVD) algorithm and two Lanczos based algorithms for sparse LSQ is compared. Several regularization methods are discussed.