DocumentCode
3373558
Title
Mean square error analyses of adaptive blind source separation algorithms
Author
Sun, Xiaoan ; Douglas, Scott C.
Author_Institution
Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA
fYear
2001
fDate
2001
Firstpage
333
Lastpage
342
Abstract
Although several simple and useful adaptive blind source separation algorithms have been developed in the scientific literature, few analyses of their second-order statistical properties have been derived. In this paper, we give the complete details of a procedure for determining the average steady-state mean square error of a blind source separation algorithm. We then apply the procedure to nine existing blind source separation algorithms employing fourth-order separation criteria. Simulation results verify the accuracy of the analysis method
Keywords
mean square error methods; signal processing; BSS; average steady-state mean square error; blind source separation; independent source signals; mean square error; mean square error methods; Algorithm design and analysis; Analytical models; Biomedical signal processing; Blind source separation; Error analysis; Mean square error methods; Riccati equations; Signal processing algorithms; Source separation; Steady-state;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop
Conference_Location
North Falmouth, MA
ISSN
1089-3555
Print_ISBN
0-7803-7196-8
Type
conf
DOI
10.1109/NNSP.2001.943138
Filename
943138
Link To Document