DocumentCode
2544726
Title
Blind Signal Separation by Entropy Maximization (INFOMAX)
Author
Jin, Qinggui ; Wang, Guirong ; Liu, Yuancheng
Author_Institution
Coll. of Inf. & Commun., Harbin Eng. Univ., Harbin, China
fYear
2010
fDate
23-25 Sept. 2010
Firstpage
1
Lastpage
5
Abstract
Independent Component Analysis (ICA) is a method of finding unknown source signals from signal mixtures, and it is just one of many solutions to the Blind Source Separation(BSS)problem. This research focuses on the "Infomax" algorithm, which finds a number of independent source signals from the same number of signal mixtures by maximizing the entropy of the signals. For small numbers of signal mixtures (two to three), the Infomax algorithm was found to be rather efficient.
Keywords
blind source separation; entropy; optimisation; principal component analysis; Infomax; blind signal separation; entropy maximization; independent component analysis; Adaptation model; Algorithm design and analysis; Educational institutions; Entropy; Equations; Independent component analysis; Mathematical model;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-3708-5
Electronic_ISBN
978-1-4244-3709-2
Type
conf
DOI
10.1109/WICOM.2010.5600111
Filename
5600111
Link To Document