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Introduction of Interpolation and Extrapolation Model in Lanczos-type Algorithms A13/B6 and A13/B13 to Enhance their Stability

机译:Lanczos型算法中的插值和外推模型引入A13 / B6和A13 / B13,提高了它们的稳定性

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摘要

A new method to treat the inherent instability of Lanczos-type algorithms is introduced. It enables us to capture the properties of the sequence of iterates generated by a Lanczos-type algorithm by interpolating on this sequence of points. The interpolation model found is then used to generate a point that is outside the range. It is expected that this new point will link up the rest of the sequence of points generated by the Lanczos-type algorithm if breakdown does not occur. However, because we assume that the interpolation model captures the properties of the Lanczos sequence, the new point belongs to that sequence since it is generated by the model. This paper introduces the so-called Embedded Interpolation and Extrapolation Model in Lanczos-type Algorithms (EIEMLA). The model was implemented in algorithms A13/B6 and A13/B13, which are new variants of the Lanczos algorithm. Individually, these algorithms perform badly on high dimensional systems of linear equations (SLEs). However, with the embedded interpolation and extrapolation models, EIEM A13/B6 and EIEM A13/B13, a substantial improvement in the performance on SLEs with up to 105 variables can be achieved.
机译:介绍了一种治疗Lanczos型算法的固有不稳定性的新方法。它使我们能够通过在该点序列上插值来捕获由Lanczos型算法生成的迭代序列的属性。然后,找到的插值模型用于生成在范围之外的点。如果未发生故障,则预计这一新点将链接Lanczos型算法生成的其余点序列。但是,由于我们假设插值模型捕获LanczoS序列的属性,因此新点属于该序列,因为它由模型生成。本文介绍了Lanczos型算法(Eiemla)中所谓的嵌入式插值和外推模型。该模型在算法A13 / B6和A13 / B13中实现,这是Lanczos算法的新变种。单独地,这些算法在线性方程(SLES)的高维系统上表现得很严重。然而,利用嵌入式插值和外推模型,Eiem A13 / B6和Eiem A13 / B13,可以实现高达105个变量的SLES性能的显着提高。

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