Independent Sub-Band Functions: Model and Applications

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. B...

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Bibliographic Details
Published in2007 International Joint Conference on Neural Networks pp. 361 - 365
Main Authors Xiefeng Cheng, Yan Zheng, Yewei Tao, Zhengyu Chen, Yuehui Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2007
Subjects
Neural networks
USA Councils
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Summary: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.
ISBN:9781424413799
1424413796
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2007.4370983