Subspace identification through blind source separation

被引：3

作者：

Grosse-Wentrup, M ^{[1
]}

Buss, M ^{[1
]}

机构：

[1] Tech Univ Munich, Inst Automat Control Engn, D-80290 Munich, Germany

来源：

IEEE SIGNAL PROCESSING LETTERS | 2006年 / 13卷 / 02期

关键词：

blind source separation (BSS); consistency; denoising; identifiability; independent component (IQ analysis; independent components; model identification; noise; stability; subspace;

D O I：

10.1109/LSP.2005.861581

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Given a linear and instantaneous mixture model, we prove that for blind source separation (BSS) algorithms based on mutual information, only sources with non-Gaussian distribution are consistently reconstructed independent of initial conditions. This allows the identification of non-Gaussian sources and consequently the identification of signal and noise subspaces through BSS. The results are illustrated with a simple example, and the implications for a variety of signal processing applications, such as denoising and model identification, are discussed.

引用

页码：100 / 103

页数：4

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