Iterative Solution Methods

  • Martin Burger
  • Barbara Kaltenbacher
  • Andreas Neubauer
Living reference work entry

Abstract

This chapter deals with iterative methods for nonlinear ill-posed problems. We present gradient and Newton type methods as well as nonstandard iterative algorithms such as Kaczmarz, expectation maximization, and Bregman iterations. Our intention here is to cite convergence results in the sense of regularization and to provide further references to the literature.

Keywords

Newton Method Source Condition Expectation Maximization Algorithm Leibler Divergence Newton Type Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Martin Burger
    • 1
  • Barbara Kaltenbacher
    • 2
  • Andreas Neubauer
    • 3
  1. 1.Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
  2. 2.Institut für MathematikAlpen-Adria-Universität KlagenfurtKlagenfurtAustria
  3. 3.Industrial Mathematics InstituteJohannes Kepler University LinzLinzAustria

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