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首页> 外文期刊>Mathematical Methods in the Applied Sciences >A fast iterative method to find the matrix geometric mean of two HPD matrices
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A fast iterative method to find the matrix geometric mean of two HPD matrices

机译:一种快速迭代方法,用于找到两个HPD矩阵的矩阵几何平均值

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摘要

>The purpose of this research is to present a novel scheme based on a quick iterative scheme for calculating the matrix geometric mean of two Hermitian positive definite (HPD) matrices. To do this, an iterative scheme with global convergence is constructed for the sign function using a novel three‐step root‐solver. It is proved that the new scheme is convergent and shown to have global convergence behavior for this target, when square matrices having no pure imaginary eigenvalues. Next, the constructed scheme is used and extended through a well‐known identity for the calculation of the matrix geometric mean of two HPD matrices. Ultimately, several experiments are collected to show its usefulness.
机译: 本研究的目的是基于快速迭代方案呈现一种新颖的方案,用于计算两个隐居正向(HPD)矩阵的矩阵几何平均值。 为此,使用新颖的三步根求解器构建具有全局收敛的迭代方案。 事实证明,新方案是收敛的,并显示该目标的全局收敛行为,当没有纯假神法值的方形矩阵时。 接下来,通过众所周知的标识来计算构造方案,以计算两个HPD矩阵的矩阵几何平均值。 最终,收集了几个实验以显示其有用性。

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