Ill-posed problems with a priori information
The book contains many new problem settings and results concerning linear and nonlinear ill-posed problems, e.g.: iteration methods based on certain quasi-non-expansive mappings (weak and strong convergence), prox-algorithm for minimization of functionals, Fejér processes, Mann processes, iterative regularization in partially ordered spaces, Gauss-Newton method; determination of a basis of the eigenspace of a linear operator corresponding to a non-isolated eigenvalue; solution of ill-posed moment problems; finite-dimensional approximation of regularized problems (the analysis is based on the discrete approximation theory by F. Stummel); self-regularization by discretization. A lot of numerical examples is presented, too.
scientific article; zbMATH DE number 844029