Tensor algorithms of blind separation of electromagnetic signals

被引：2
|
作者：
Savostyanov, D. V. [1 ]
机构：
[1] Russian Acad Sci, Inst Numer Math, Moscow 119333, Russia
来源：
RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING | 2010年 / 25卷 / 04期
基金：
俄罗斯基础研究基金会;
关键词：
REDUCTION; COMPUTATION; SYSTEMS; COMPLEX; RANK;
D O I：
10.1515/RJNAMM.2010.024
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The problem of blind separation of electromagnetic signals is reduced to joint diagonalization of a set of matrices-statistics. For the solution of this problem we propose complex versions of tensor decomposition algorithms based on the multiplicative update and on the supergeneralized Schur decomposition. A comparison of the obtained results with algorithms of FastICA type is performed and the advantage of tensor methods in the packet signal processing mode is discussed.
引用
收藏
页码：375 / 393
页数：19
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