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首页> 外文期刊>SIAM Journal on Matrix Analysis and Applications >Solving the indefinite least squares problem by hyperbolic QR factorization
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Solving the indefinite least squares problem by hyperbolic QR factorization

机译:用双曲QR分解法求解不定最小二乘问题

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摘要

The indefinite least squares (ILS) problem involves minimizing a certain type of indefinite quadratic form. We develop perturbation theory for the problem and identify a condition number. We describe and analyze a method for solving the ILS problem based on hyperbolic QR factorization. This method has a lower operation count than one recently proposed by Chandrasekaran, Gu, and Sayed that employs both QR and Cholesky factorizations. We give a rounding error analysis of the new method and use the perturbation theory to show that under a reasonable assumption the method is forward stable. Our analysis is quite general and sheds some light on the stability properties of hyperbolic transformations. In our numerical experiments the new method is just as accurate as the method of Chandrasekaran, Gu, and Sayed. [References: 18]
机译:不定最小二乘(ILS)问题涉及最小化某种类型的不定二次型。我们针对该问题开发微扰理论,并确定条件数。我们描述和分析了一种基于双曲QR分解的ILS问题解决方法。与Chandrasekaran,Gu和Sayed最近提出的同时使用QR和Cholesky因子分解的方法相比,该方法的运算数量更少。我们对该新方法进行了舍入误差分析,并使用扰动理论表明,在合理的假设下,该方法是前向稳定的。我们的分析相当笼统,并为双曲变换的稳定性提供了一些启示。在我们的数值实验中,新方法与Chandrasekaran,Gu和Sayed的方法一样准确。 [参考:18]

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