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 :
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