• Media type: Text; E-Article
  • Title: Enhancing linear regularization to treat large noise
  • Contributor: Mathé, Peter [Author]; Tautenhahn, Ulrich [Author]
  • Published: Weierstrass Institute for Applied Analysis and Stochastics publication server, 2011
  • Language: English
  • DOI: https://doi.org/10.1515/JIIP.2011.052
  • ISSN: 0928-0219
  • Keywords: Ill-posed problems -- inverse problems -- regularization -- Hilbert scales -- order optimal error bounds -- large noise -- small noise ; article ; 65J20 ; 47A52
  • Origination:
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  • Description: For solving linear ill-posed problems with noisy data, regularization methods are required. In this paper we study regularization under general noise assumptions containing large noise and small noise as special cases. We derive order optimal error bounds for an extended Tikhonov regularization by using some pre-smoothing. This accompanies recent results by the same authors, Regularization under general noise assumptions, Inverse Problems 27:3, 035016, 2011.
  • Access State: Open Access