Landweber iteration is an iterative method used to solve linear inverse problems, particularly when dealing with ill-posed problems. This technique aims to approximate a solution by iteratively refining an estimate based on the residuals of the linear operator applied to the current approximation, effectively minimizing the difference between observed and predicted data. It connects to various strategies for regularization and convergence analysis in both linear and non-linear contexts.
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