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Regularizing preconditioners by non-stationary iterated Tikhonov with general penalty term

机译:通过具有固定惩罚期限的非平稳迭代Tikhonov来对预处理器进行正则化

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摘要

The nonstationary preconditioned iteration proposed in a recent work by Donatelli and Hanke appeared on IP can be seen as an approximated iterated Tikhonov method. Starting from this observation we extend the previous iteration in two directions: the introduction of a regularization operator different from the identity (e.g., a differential operator) and the projection into a convex set (e.g., the nonnegative cone). Depending on the application both generalizations can lead to an improvement in the quality of the computed approximations. Convergence results and regularization properties of the proposed iterations are proved. Finally, the new methods are applied to image deblurring problems and compared with the iteration in the original work and other methods with similar properties recently proposed in the literature.
机译:Donatelli和Hanke在IP上发表的最新著作中提出的非平稳预条件迭代可以看作是近似的Tikhonov方法。从这一观察开始,我们在两个方向上扩展了先前的迭代:引入了不同于恒等式的正则化算子(例如,微分算子)和投影到凸集(例如,非负锥)中。取决于应用,两种概括都可以导致所计算的近似值的质量的提高。证明了所提出迭代的收敛结果和正则化性质。最后,将新方法应用于图像去模糊问题,并将其与原始工作中的迭代以及文献中最近提出的具有类似特性的其他方法进行比较。

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