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A GCV based Arnoldi-Tikhonov regularization method

机译:基于GCV的Arnoldi-Tikhonov正则化方法

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摘要

For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhonov method coupled with the Generalized Cross Validation for the computation of the regularization parameter at each iteration. We study the convergence behavior of the Arnoldi method and its properties for the approximation of the (generalized) singular values, under the hypothesis that Picard condition is satisfied. Numerical experiments on classical test problems and on image restoration are presented.
机译:对于线性离散不适定问题的解决方案,在本文中,我们考虑将Arnoldi-Tikhonov方法与广义交叉验证相结合,以便在每次迭代时计算正则化参数。在满足皮卡德条件的假设下,我们研究了Arnoldi方法的收敛行为及其(广义)奇异值逼近的性质。提出了关于经典测试问题和图像复原的数值实验。

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