@unpublished{DickenMaass1995,
  author    = {Dicken, Volker and Maaß, Peter},
  title     = {Wavelet-Galerkin methods for ill-posed problems},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-13890},
  year      = {1995},
  abstract  = {Projection methods based on wavelet functions combine optimal convergence rates with algorithmic efficiency. The proofs in this paper utilize the approximation properties of wavelets and results from the general theory of regularization methods. Moreover, adaptive strategies can be incorporated still leading to optimal convergence rates for the resulting algorithms. The so-called wavelet-vaguelette decompositions enable the realization of especially fast algorithms for certain operators.},
  language  = {en}
}
@unpublished{MaassPereverzevRamlauetal.1998,
  author    = {Maaß, Peter and Pereverzev, Sergei V. and Ramlau, Ronny and Solodky, Sergei G.},
  title     = {An adaptive discretization for Tikhonov-Phillips regularization with a posteriori parameter selection},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-14739},
  year      = {1998},
  abstract  = {The aim of this paper is to describe an efficient strategy for descritizing ill-posed linear operator equations of the first kind: we consider Tikhonov-Phillips-regularization χ^δ α = (a * a + α I)^-1 A * y ^δ with a finite dimensional approximation A n instead of A. We propose a sparse matrix structure which still leads to optimal convergences rates but requires substantially less scalar products for computing A n compared with standard methods.},
  language  = {en}
}
@unpublished{MaassRieder1996,
  author    = {Maaß, Peter and Rieder, Andreas},
  title     = {Wavelet-accelerated Tikhonov-Phillips regularization with applications},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-14104},
  year      = {1996},
  abstract  = {Contents: 1 Introduction 1.1 Tikhanov-Phillips Regularization of Ill-Posed Problems 1.2 A Compact Course to Wavelets 2 A Multilevel Iteration for Tikhonov-Phillips Regularization 2.1 Multilevel Splitting 2.2 The Multilevel Iteration 2.3 Multilevel Approach to Cone Beam Reconstuction 3 The use of approximating operators 3.1 Computing approximating families {Ah}},
  language  = {en}
}