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An algorithm for automatically selecting a suitable verification method for linear systems

机译:自动选择适用于线性系统的验证方法的算法

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Several methods have been proposed to calculate a rigorous error bound of an approximate solution of a linear system by floating-point arithmetic. These methods are called ‘verification methods’. Applicable range of these methods are different. It depends mainly on the condition number and the dimension of the coefficient matrix whether such methods succeed to work or not. In general, however, the condition number is not known in advance. If the dimension or the condition number is large to some extent, then Oishi–Rump’s method, which is known as the fastest verification method for this purpose, may fail. There are more robust verification methods whose computational cost is larger than the Oishi–Rump’s one. It is not so efficient to apply such robust methods to well-conditioned problems. The aim of this paper is to choose a suitable verification method whose computational cost is minimum to succeed. First in this paper, four fast verification methods for linear systems are briefly reviewed. Next, a compromise method between Oishi–Rump’s and Ogita–Oishi’s one is developed. Then, an algorithm which automatically and efficiently chooses an appropriate verification method from five verification methods is proposed. The proposed algorithm does as much work as necessary to calculate error bounds of approximate solutions of linear systems. Finally, numerical results are presented.
机译:已经提出了几种通过浮点算法来计算线性系统的近似解的严格误差范围的方法。这些方法称为“验证方法”。这些方法的适用范围不同。这些方法是否成功,主要取决于条件数和系数矩阵的维数。但是,一般而言,条件编号是事先未知的。如果维数或条件数在某种程度上较大,则Oishi–Rump的方法(为此目的被称为最快的验证方法)可能会失败。有更强大的验证方法,其计算成本比Oishi–Rump的计算成本高。将这种鲁棒的方法应用于条件良好的问题并不是很有效。本文的目的是选择一种计算成本最小的合适验证方法来成功。本文首先简要回顾了线性系统的四种快速验证方法。接下来,开发了一种在Oishi-Rump公司与Ogita-Oishi公司之间的折衷方法。然后,提出了一种从五种验证方法中自动有效选择合适的验证方法的算法。所提出的算法在计算线性系统的近似解的误差范围时做了很多必要的工作。最后,给出了数值结果。

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