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
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;
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
DOI :
10.1109/WICOM.2010.5600111
