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Hermitian tridiagonal solution with the least norm to quaternionic least squares problem

机译:具有最小范数到四元数最小二乘问题的厄米三对角线解

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摘要

Quaternionic least squares (QLS) is an efficient method for solving approximate problems in quaternionic quantum theory. In view of the extensive applications of Hermitian tridiagonal matrices in physics, in this paper we list some properties of basis matrices and subvectors related to tridiagonal matrices, and give an iterative algorithm for finding Hermitian tridiagonal solution with the least norm to the quaternionic least squares problem by making the best use of structure of real representation matrices, we also propose a preconditioning strategy for the Algorithm LSQR-Q in Wang, Wei and Feng (2008) [14] and our algorithm. Numerical experiments are provided to verify the effectiveness of our method.
机译:四元数最小二乘(QLS)是解决四元数论量子理论中近似问题的一种有效方法。鉴于厄米三对角矩阵在物理学中的广泛应用,本文列出了与三对角矩阵相关的基本矩阵和子向量的一些性质,并给出了一种迭代算法,该算法可找到四元数最小二乘问题具有最小范数的厄米三对角解通过充分利用实数表示矩阵的结构,我们还为Wang,Wei和Feng(2008)[14]中的算法LSQR-Q和我们的算法提出了一种预处理策略。提供数值实验以验证我们方法的有效性。

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