Householder orthogonalization plays an important role in numerical linear algebra. It attains perfect orthogonality regardless of the conditioning of the input. However, in the context of a non-standard inner product, it becomes difficult to apply Householder orthogonalization due to the lack of an initial orthonormal basis. We propose strategies to overcome this obstacle and discuss algorithms and variants of Householder orthogonalization with a non-standard inner product. Theoretical analysis and numerical experiments demonstrate that our approach is numerically stable under mild assumptions.
翻译:家居直线代数在数字直线代数中起着重要作用,无论输入的附加条件如何,它都能达到完美的正数。然而,在非标准内产物中,由于缺乏初始的正正态基础,因此难以应用家居正数正数。我们提出了克服这一障碍的战略,并与非标准内产物讨论了家居正数正数的算法和变体。理论分析和数字实验表明,在轻度假设下,我们的方法在数字上是稳定的。