DocumentCode
2244535
Title
Blind signal separation using ICA
Author
Zhou, Weidong ; Jia, Lei
Author_Institution
Sch. of Inf. Sci., Shandong Univ., Jinan, China
Volume
4
fYear
2001
fDate
2001
Firstpage
237
Abstract
In this paper, a steepest descent algorithm for independent component analysis (ICA) is proposed. In contrast to most blind source separation algorithms, the method does not employ higher order statistics. A pre-whitening procedure is performed to de-correlate the sensor (mixed) signals before extracting the vector. The proposed method is verified with computer simulation
Keywords
decorrelation; entropy; neural nets; signal processing; statistical analysis; ICA; blind signal separation; blind source separation; decorrelation; entropy; independent component analysis; neural network; pre-whitening procedure; steepest descent algorithm; Blind source separation; Data mining; Entropy; Higher order statistics; Independent component analysis; Multidimensional signal processing; Neural networks; Random variables; Signal processing algorithms; Source separation;
fLanguage
English
Publisher
ieee
Conference_Titel
Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
Conference_Location
Beijing
Print_ISBN
0-7803-7010-4
Type
conf
DOI
10.1109/ICII.2001.983824
Filename
983824
Link To Document