Regularization in Banach spaces - convergence rates by approximative source conditions

In this paper we deal with convergence rates for a Tikhonov regularization approach for linear and nonlinear ill-posed problems in Banach spaces. Here, we deal with so-called distance functions which quantify the violation of a given reference source condition. With the aid of these functions we present error bounds and convergence rates for regularized solutions of linear and nonlinear problems when the reference source condition is violated. Introducing this topic for linear problems we extend the theory also to nonlinear problems. Finally an a-posteriori choice of the regularization parameter is suggested yielding the optimal convergence rate.