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On the structured backward error of inexact Arnoldi methods for (skew)-Hermitian and (skew)-symmetric eigenvalue problems

机译:关于(偏)-Hermitian和(偏)对称特征值问题的不精确Arnoldi方法的结构化后向误差

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摘要

In this paper, we present the inexact structure preserving Arnoldi methods for structured eigenvalue problems. They are called structure preserving because the computed eigenvalues and eigenvectors can preserve the desirable properties of the structures of the original matrices, even with large errors involved in the computation of matrix-vector products. A backward error matrix is called structured if it has the same structure as the original matrix. We derive a common form for the structured backward errors that can be used for different structure preserving processes, and prove the derived form has the minimum Frobenius norm among all possible backward errors. Furthermore, we employ the derived backward errors for some specific structure preserving processes to estimate the accuracy of the solutions obtained by inexact Arnoldi methods for eigenvalue problems. We aim to give, wherever possible, formulae that are inexpensive to compute so that they can be used routinely in practice. Numerical experiments are provided to support the theoretical results.
机译:在本文中,我们提出了用于结构化特征值问题的不精确结构保留Arnoldi方法。之所以称它们为结构保留,是因为计算出的特征值和特征向量可以保留原始矩阵结构的理想属性,即使矩阵向量乘积的计算中存在很大的误差。如果后向误差矩阵的结构与原始矩阵相同,则称其为结构化。我们为结构化后向误差推导了一种通用形式,可用于不同的结构保留过程,并证明该推导形式在所有可能的向后误差中具有最小的Frobenius范数。此外,我们将导出的向后误差用于某些特定的结构保留过程,以估计通过不精确的Arnoldi方法获得的特征值问题解的准确性。我们的目标是尽可能提供不昂贵的公式,以便可以在实践中常规使用。提供数值实验以支持理论结果。

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