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Jacobi like algorithm for non-orthogonal joint diagonalization of hermitian matrices

机译:Hermitian矩阵非正交联合对角化的Jacobi样算法

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In this paper, we consider the problem of non-orthogonal joint diagonalization of a set of hermitian matrices. This appears in many blind signal processing problems as source separation and independent component analysis. We propose a new Jacobi like algorithm based on a LU decomposition. The main point consists of the analytical derivation of the elementary two by two matrix. In order to determine the diagonalizing matrix parameters, we propose a useful approximation. Numerical simulations illustrate the overall good performances of the proposed algorithm in comparison to two other Jacobi like algorithms existing in the literature.
机译:在本文中,我们考虑了一组厄米矩阵的非正交联合对角化问题。这出现在许多盲信号处理问题中,例如源分离和独立成分分析。我们提出了一种新的基于LU分解的Jacobi类算法。要点包括基本二乘二矩阵的解析推导。为了确定对角矩阵参数,我们提出了一个有用的近似值。数值模拟表明,与文献中存在的其他两种类似Jacobi的算法相比,该算法总体上具有良好的性能。

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