Variational smoothness assumptions in convergence rate theory—an overview

Variational smoothness assumptions are a concept for measuring abstract smoothness of solutions to operator equations. Such assumptions are useful for analyzing regularization methods, especially for proving convergence rates in Banach spaces and in more general settings. We collect results from different papers published by several authors during the last five years. The aim is to present an overview of this relatively new concept to the interested reader without going too deep into the details. 1 Ill-posed problems, regularization, convergence rates A frequently used model for practical problems are equations F (x) = y, x ∈ dom(F ) ⊆ X, y ∈ Y (1.1) between Banach spaces X and Y . The exact right-hand side y is typically unknown. Instead, only noisy data yδ ∈ Y satisfying ‖y − yδ‖ ≤ δ are available. The noise level is quantified by δ ≥ 0. For solving such equations numerically the mapping F : dom(F ) → Y has to have nice properties. ∗Chemnitz University of Technology, Department of Mathematics, D-09107 Chemnitz, Germany, jens.flemming@mathematik.tu-chemnitz.de.

[1]  B. Hofmann Approximate source conditions in Tikhonov–Phillips regularization and consequences for inverse problems with multiplication operators , 2006 .

[2]  Andreas Neubauer,et al.  On enhanced convergence rates for Tikhonov regularization of nonlinear ill-posed problems in Banach spaces , 2009 .

[3]  Bernd Hofmann,et al.  Parameter choice in Banach space regularization under variational inequalities , 2012 .

[4]  Jens Flemming,et al.  Generalized Tikhonov regularization , 2011 .

[5]  Barbara Kaltenbacher,et al.  Iterative Regularization Methods for Nonlinear Ill-Posed Problems , 2008, Radon Series on Computational and Applied Mathematics.

[6]  Bernd Hofmann,et al.  On the interplay of source conditions and variational inequalities for nonlinear ill-posed problems , 2010 .

[7]  Otmar Scherzer,et al.  The residual method for regularizing ill-posed problems , 2009, Appl. Math. Comput..

[8]  Jens Flemming,et al.  Sharp converse results for the regularization error using distance functions , 2011 .

[9]  Markus Grasmair,et al.  Convergence Rates for Tikhonov Regularisation on Banach Spaces , 2011 .

[10]  Radu Ioan Bot,et al.  An extension of the variational inequality approach for nonlinear ill-posed problems , 2009 .

[11]  Bernd Hofmann,et al.  How general are general source conditions? , 2008 .

[12]  Otmar Scherzer,et al.  Variational Methods in Imaging , 2008, Applied mathematical sciences.

[13]  Jens Flemming,et al.  Convergence rates in constrained Tikhonov regularization: equivalence of projected source conditions and variational inequalities , 2011 .

[14]  Bernd Hofmann,et al.  Approximate source conditions for nonlinear ill-posed problems—chances and limitations , 2009 .

[15]  M. Grasmair Generalized Bregman distances and convergence rates for non-convex regularization methods , 2010 .

[16]  Jens Flemming,et al.  Theory and examples of variational regularization with non-metric fitting functionals , 2010 .

[17]  Andreas Neubauer,et al.  Tikhonov-regularization of ill-posed linear operator equations on closed convex sets , 1988 .

[18]  B. Hofmann,et al.  Convergence rates for the iteratively regularized Gauss–Newton method in Banach spaces , 2010 .

[19]  Torsten Hein,et al.  Tikhonov regularization in Banach spaces—improved convergence rates results , 2009 .

[20]  Bernd Hofmann,et al.  Analysis of Profile Functions for General Linear Regularization Methods , 2007, SIAM J. Numer. Anal..

[21]  S. Osher,et al.  Convergence rates of convex variational regularization , 2004 .

[22]  K. Bredies,et al.  Regularization with non-convex separable constraints , 2009 .

[23]  Martin Burger,et al.  Convergence rates in $\mathbf{\ell^1}$-regularization if the sparsity assumption fails , 2012 .

[24]  Jens Flemming,et al.  A New Approach to Source Conditions in Regularization with General Residual Term , 2009 .

[25]  A. Neubauer,et al.  Improved and extended results for enhanced convergence rates of Tikhonov regularization in Banach spaces , 2010 .

[26]  O. Scherzer,et al.  A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators , 2007 .

[27]  Barbara Kaltenbacher,et al.  Regularization Methods in Banach Spaces , 2012, Radon Series on Computational and Applied Mathematics.

[28]  H. Engl,et al.  Regularization of Inverse Problems , 1996 .