仿射迭代和包裹效应:各种方法

N. Revol
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引用次数: 0

摘要

如果矩阵A的谱半径小于1,则形式为xn+1=Axn+b的仿射迭代使用实算法收敛。但是,将区间算法替换为实数算法可能会导致这些迭代的发散,特别是当A的绝对值的谱半径大于1时。当初始向量x(0)和b的分量是区间时,我们将回顾不同的方法来限制迭代的高估。我们将从理论上和实验上比较这些不同方法计算的迭代宽度:朴素迭代,基于A的QR和svd分解的方法,以及Lohner的QR分解方法。基于奇异值分解的方法计算量小,在矩阵尺度较差的情况下能得到较好的结果,否则可被朴素迭代法或Lohner方法所取代。
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Affine Iterations and Wrapping Effect: Various Approaches
Affine iterations of the form xn+1=Axn+b converge, using real arithmetic, if the spectral radius of the matrix A is less than 1. However, substituting interval arithmetic to real arithmetic may lead to divergence of these iterations, in particular if the spectral radius of the absolute value of A is greater than 1. We will review  different approaches to limit the overestimation of the iterates, when the components of the initial vector x(0) and b are intervals. We will compare, both theoretically and experimentally, the widths of the iterates computed by these different methods: the naive iteration, methods based on the QR- and SVD-factorization of A, and Lohner's QR-factorization method. The method  based on the SVD-factorization is computationally less demanding and gives good results when the matrix is poorly scaled, it is superseded either by the naive iteration or by Lohner's method otherwise.
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