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New Jacobi-like algorithms for non-orthogonal joint diagonalization of Hermitian matrices

机译:Hermitian矩阵非正交联合对角化的新Jacobi类算法

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In this paper, two new algorithms are proposed for non-orthogonal joint matrix diagonalization under Hermitian congruence. The idea of these two algorithms is based on the so-called Jacobi algorithm for solving the eigenvalues problem of Hermitian matrix. The algorithms are then called 'general Jabobi-like diagonalization' algorithms (GERALD). They are based on the search of two complex parameters by the minimization of a quadratic criterion corresponding to a measure of diagonality. Lastly, numerical simulations are conducted to illustrate the effective performances of the GERALD algorithms.
机译:本文针对Hermitian同余提出了两种新的非正交联合矩阵对角化算法。这两种算法的思想是基于所谓的雅可比(Jacobi)算法,用于解决厄米矩阵的特征值问题。然后将这些算法称为“通用Jabobi样对角化”算法(GERALD)。它们基于最小化与对角线量度相对应的二次标准来搜索两个复杂参数。最后,进行了数值模拟,以说明GERALD算法的有效性能。

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