Landweber–Kaczmarz for parameter identification in time-dependent inverse problems: all-at-once versus reduced version

In this study, we consider a general time-space system, whose model operator and observation operator are locally Lipschitz continuous, over a finite time horizon and parameter identification by using Landweber–Kaczmarz regularization. The problem is investigated in two different modeling settings: an all-at-once and a reduced version, together with two observation scenarios: continuous and discrete observations. Segmenting the time line into several subintervals leads to the idea of applying the Kaczmarz method. A loping strategy is incorporated into the method to yield the loping Landweber–Kaczmarz iteration. (paper)