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