Convergence analysis of a block iterative version of the loping Landweber–Kaczmarz iteration Original Research Article

The loping Landweber–Kaczmarz iteration is a numerically efficient regularization method for solving ill-posed problems. In this article we investigate a block iterative version that allows variable block sizes and variable grouping of the sub-equations during the iterations. We show that the proposed method converges for exact data and is a strongly convergent regularization method for noisy data.