Fully-Complex Infomax for Blind Separation of Delayed Sources

Zongli RUAN  Ping WEI  Guobing QIAN  Hongshu LIAO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E99-A   No.5   pp.973-977
Publication Date: 2016/05/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E99.A.973
Type of Manuscript: LETTER
Category: Digital Signal Processing
Keyword: 
blind source separation (BSS),  fully-complex infomax,  feedback network,  delayed source,  measurement matrix,  

Full Text: PDF>>
Buy this Article




Summary: 
The information maximization (Infomax) based on information entropy theory is a class of methods that can be used to blindly separate the sources. Torkkola applied the Infomax criterion to blindly separate the mixtures where the sources have been delayed with respect to each other. Compared to the frequency domain methods, this time domain method has simple adaptation rules and can be easily implemented. However, Torkkola's method works only in the real valued field. In this letter, the Infomax for blind separation of the delayed sources is extended to the complex case for processing of complex valued signals. Firstly, based on the gradient ascent the adaptation rules for the parameters of the unmixing network are derived and the steps of algorithm are given. Then, a measurement matrix is constructed to evaluate the separation performance. The results of computer experiment support the extended algorithm.