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Computable upper error bounds for Krylov approximations to matrix exponentials and associated φ-functions

机译:矩阵指数和相关φ函数的Krylov逼近的可计算误差上限

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An a posteriori estimate for the error of a standard Krylov approximation to the matrix exponential is derived. The estimate is based on the defect (residual) of the Krylov approximation and is proven to constitute a rigorous upper bound on the error, in contrast to existing asymptotical approximations. It can be computed economically in the underlying Krylov space. In view of time-stepping applications, assuming that the given matrix is scaled by a time step, it is shown that the bound is asymptotically correct (with an order related to the dimension of the Krylov space) for the time step tending to zero. This means that the deviation of the error estimate from the true error tends to zero faster than the error itself. Furthermore, this result is extended to Krylov approximations of phi-functions and to improved versions of such approximations. The accuracy of the derived bounds is demonstrated by examples and compared with different variants known from the literature, which are also investigated more closely. Alternative error bounds are tested on examples, in particular a version based on the concept of effective order. For the case where the matrix exponential is used in time integration algorithms, a step size selection strategy is proposed and illustrated by experiments.
机译:得出了标准Krylov近似值对矩阵指数的误差的后验估计。该估计基于Krylov近似的缺陷(残差),并且与现有的渐近近似相反,该估计被证明构成误差的严格上限。可以在潜在的Krylov空间中经济地进行计算。考虑到时间步长的应用,假设给定的矩阵按时间步长进行缩放,则表明对于趋于零的时间步长,边界是渐近正确的(与Krylov空间的维数有关)。这意味着误差估计值与真实误差的偏差趋于比误差本身快零。此外,该结果扩展到phi函数的Krylov逼近和此类逼近的改进版本。实例证明了导出边界的准确性,并与文献中已知的不同变体进行了比较,这些变体也进行了更深入的研究。在示例中测试了可选的错误界限,尤其是基于有效顺序概念的版本。对于在时间积分算法中使用矩阵指数的情况,提出了步长选择策略并通过实验进行了说明。

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