DocumentCode
3174636
Title
A new algorithm of Infomax for small numbers of sound signal separation
Author
Qinggui Jin ; Liang, Guolong
Author_Institution
Coll. of Inf. & Commun., Harbin Eng. Univ., Harbin, China
fYear
2010
fDate
29-30 Oct. 2010
Firstpage
159
Lastpage
162
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 is found to be rather efficient.
Keywords
blind source separation; entropy; independent component analysis; BSS problem; ICA; Infomax algorithm; blind source separation; entropy; independent component analysis; independent source signals; signal mixtures; sound signal separation; unknown source signals; Chirp; Entropy; Ions; Presses; BSS; ENTROPY; ICA; INFOMAX;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence and Education (ICAIE), 2010 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-6935-2
Type
conf
DOI
10.1109/ICAIE.2010.5641410
Filename
5641410
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