Iterative Regularization Methods for Nonlinear Ill-Posed Problems

Nonlinear inverse problems result from 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. From the contents: Nonlinear Landweber iteration Modified Landweber methods Newton type methods Multilevel methods Level set methods Applications