A two-point gradient method for nonlinear ill-posed problemsMS62

We present and analyse a class of gradient based iterative methods for solving nonlinear ill-posed problems which are inspired by Landweber iteration and Nesterov's acceleration scheme and promise to be good alternatives to second order methods. The usefulness of these methods is demonstrated on a numerical example problems based on the nonlinear inverse problem of single photon emission computed tomography (SPECT).

This presentation is part of Minisymposium “MS62 - Imaging models with non-linear constraints (2 parts)
organized by: Tuomo Valkonen (University of Liverpool) , Juan Carlos De Los Reyes (Escuela Politécnica Nacional) .

Simon Hubmer (Johannes Kepler University Linz)
Ronny Ramlau (Kepler University Linz and Johann Radon Institute)
computed tomography, inverse problems, nonlinear optimization