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
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;
Conference_Titel :
Artificial Intelligence and Education (ICAIE), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-6935-2
DOI :
10.1109/ICAIE.2010.5641410