@inproceedings{Kunoth,
  author    = {Kunoth, Angela},
  title     = {MULTISCALE ANALYSIS OF MULTIVARIATE DATA},
  editor    = {G{\"u}rlebeck, Klaus and K{\"o}nke, Carsten},
  organization    = {Bauhaus-Universit{\"a}t Weimar},
  issn      = {1611-4086},
  doi       = {10.25643/bauhaus-universitaet.2864},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28644},
  pages     = {20},
  abstract  = {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.},
  subject      = {Angewandte Informatik},
  language  = {en}
}