Ill-posed problems (1) are considered, where is a linear operator between Hilbert spaces and . It is supposed that equation (1) has a minimum norm solution that satisfies a logarithmic source condition of the form (2) , where for with some real parameter , and a scaling is assumed.
For the stable solution of equation (1) with a minimum norm solution that satisfies such a logarithmic source condition (2), the author considers a priori and a posteriori parameter choice strategies for regularization methods of the general form (2) . Here is a perturbation of the exact right-hand side with . Moreover it is supposed that () are given functions such that, for each , we have as . Under certain additional conditions on the mappings , order optimal convergence rates of the form are obtained for each considered parameter choice , where holds.
The considered class of regularization methods contains well-known regularization methods like the Tikhonov regularization and the Landweber iteration, for example. This class of regularization methods is considered also to solve a class of nonlinear ill-posed problems. It is supposed here that the underlying nonlinear operator is given approximately by some linear operator, and moreover it is supposed that the solution to this nonlinear equation exists and satisfies a generalized logarithmic source condition.
For a second class of nonlinear ill-posed problems the iteratively regularized Gauss-Newton method is considered. Finally it is shown that the obtained results can be applied to specific problems like the backwards heat equation and the sideways heat equation, respectively.