A general merit function-based global convergent framework for nonlinear optimization

In this paper, we revisit the convergence theory of the inexact restoration paradigm for non-linear optimization. The paper first identifies the basic elements of a globally convergent method based on merit functions. Then, the inexact restoration method that employs a two-phase iteration is introduced as a special case. A specific implementation is presented that is … Read more

Under-relaxed Quasi-Newton acceleration for an inverse fixed-point problem coming from Positron-Emission Tomography

Quasi-Newton acceleration is an interesting tool to improve the performance of numerical methods based on the fixed-point paradigm. In this work the quasi-Newton technique will be applied to an inverse problem that comes from Positron Emission Tomography, whose fixed-point counterpart has been introduced recently. It will be shown that the improvement caused by the quasi-Newton … Read more