Refine
Document Type
- Conference Proceeding (145) (remove)
Institute
- In Zusammenarbeit mit der Bauhaus-Universität Weimar (82)
- Graduiertenkolleg 1462 (31)
- Institut für Strukturmechanik (ISM) (12)
- Professur Angewandte Mathematik (12)
- Institut für Konstruktiven Ingenieurbau (IKI) (4)
- Professur Informatik im Bauwesen (4)
- Professur Stochastik und Optimierung (3)
- Professur Computer Vision in Engineering (2)
- Professur Stahlbau (2)
- Institut für Bauinformatik, Mathematik und Bauphysik (IBMB) (1)
Keywords
- Angewandte Informatik (145) (remove)
For many applications, nonuniformly distributed functional data is given which lead to large–scale scattered data problems. We wish to represent the data in terms of a sparse representation with a minimal amount of degrees of freedom. For this, an adaptive scheme which operates in a coarse-to-fine fashion using a multiscale basis is proposed. Specifically, we investigate hierarchical bases using B-splines and spline-(pre)wavelets. At each stage a leastsquares approximation of the data is computed. We take into account different requests arising in large-scale scattered data fitting: we discuss the fast iterative solution of the least square systems, regularization of the data, and the treatment of outliers. A particular application concerns the approximate continuation of harmonic functions, an issue arising in geodesy.