DocumentCode
1941159
Title
Independent Sub-Band Functions: Model and Applications
Author
Cheng, Xiefeng ; Zheng, Yan ; Tao, Yewei ; Chen, Zhengyu ; Chen, Yuehui
Author_Institution
Univ. of Jinan, Jinan
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
361
Lastpage
365
Abstract
The paper presented a new signal processing technique to accomplish blind source separation when given only a single-channel mixture signal. One signal source can be generated by a set of weighted linear superposition of the time domain sub-band functions with independent component characteristic. By combining the independent sub-band function components into the single-channel mixture signal, making the single-channel mixture signal is transformed into a multi-dimensional vector from one-dimensional. Thus ICA can be applied to separate the extended single-channel mixture signal. The simulation results demonstrated the effectiveness and adaptability of the proposed method. What is more, similitude phase graph is also proposed in this paper, which can show the performance of blind separation algorithm straightly.
Keywords
blind source separation; independent component analysis; ICA; blind separation algorithm; blind source separation; independent component characteristic; independent sub-band functions:; multi-dimensional vector; signal processing technique; single-channel mixture signal; time domain sub-band functions; weighted linear superposition; Neural networks; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4370983
Filename
4370983
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