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A multi-grid method with a priori and a posteriori level choice for the regularization of nonlinear ill-posed problems

机译:具有先验和后验水平选择的多网格方法用于非线性不适定问题的正则化

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In this paper we study a multi-grid method for the numerical solution of nonlinear systems of equations arising from the discretization of ill-posed problems, where the special eigensystem structure of the underlying operator equation makes it necessary to use special smoothers. We provide uniform contraction factor estimates and show that a nested multi-grid iteration together with an a priori or a posteriori chosen stopping index defines a regularization method for the ill-posed problem, i.e., a stable solution method, that converges to an exact solution of the underlying infinite-dimensional problem as the data noise level goes to zero, with optimal rates under additional regularity conditions. [References: 28]
机译:在本文中,我们研究了不适定问题离散化引起的非线性方程组数值解的多重网格方法,其中底层算子方程的特殊本征系统结构使得有必要使用特殊的平滑器。我们提供统一的收缩因子估计,并表明嵌套的多网格迭代与先验或后验选择的停止索引一起定义了不适定问题的正则化方法,即稳定解法,该方法收敛到精确解随着数据噪声水平趋于零,在附加规则性条件下具有最佳速率时,潜在的无限维问题的解决方案。 [参考:28]

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