JACOBI LIKE ALGORITHM FOR NON-ORTHOGONAL JOINT DIAGONALIZATION OF HERMITIAN MATRICES

被引：0
作者：
Maurandi, Victor [1 ]
Moreau, Eric [1 ]
De Luigi, Christophe [1 ]
机构：
[1] Aix Marseille Univ, CNRS, ENSAM, LSIS,UMR 7296, F-13397 Marseille, France
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2014年
关键词：
Blind source separation; Independent component analysis; Jacobi algorithm; Joint diagonalization; BLIND SOURCE SEPARATION;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
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.
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页数：5
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