Andreas Neubauer

Otmar Scherzer

Barbara Kaltenbacher

Nonlinear inverse problems appear in many applications, and typically they lead to mathematical models that are ill-posed, i.e., they are unstable under data perturbations. Those problems require a regularization, i.e., a special numerical treatment. This book presents regularization schemes which are based on iteration methods, e.g., nonlinear Landweber iteration, level set methods, multilevel methods and Newton type methods.

Books like Iterative Regularization Methods for Nonlinear Ill-Posed Problems

Your next favorite book is out there