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International Symposium on Neural Networks

ISNN 2008: Advances in Neural Networks - ISNN 2008 pp 650–657Cite as

A New BSS Method of Single-Channel Mixture Signal Based on ISBF and Wavelet

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5264))

Abstract

A new BSS method based on independent sub-band function components (ISBF) and wavelet to separate single-channel mixture signal in noise was studied. Through obtaining sub-band functions with independent component characteristic in the time domain, 6-20 sub-band function by ICA were employed as the preparation knowledge for the blind source separation (BSS). By combining the independent sub-band function components (ISBF) into the single-channel mixture signal, a separation modeling of single-channel mixture signal was built based on ISBF. And the separation mathematics model of the single-channel signal in noise is investigated. The wavelet transform was used to eliminate the noise as well. Two simulation samples performed to verify the availability of the proposed methods. The results show that the methods played good role in one sensor source BSS, and had a capability to extract the sound signal feature.

 This research was supported by the Provincial Natural Science Foundation and Science and Technology Tackle Key Problem of Shandong (No.Y2006G03, No.Y2007G14, No.2006Gg3204005, No.2007Jy17), and Science Foundation of Nanjing University of Posts & Telecommunications (NY207139).

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Author information

Authors and Affiliations

  1. Nanjing University of Posts & Telecommunications, Nanjing, 210003, P.R. China

    Xiefeng Cheng, Yewei Tao, Yufeng Guo & Xuejun Zhang

  2. Jinan University, Jinan, 250100, P.R. China

    Xiefeng Cheng & Yewei Tao

Authors
  1. Xiefeng Cheng
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  2. Yewei Tao
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  3. Yufeng Guo
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  4. Xuejun Zhang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Cite this paper

Cheng, X., Tao, Y., Guo, Y., Zhang, X. (2008). A New BSS Method of Single-Channel Mixture Signal Based on ISBF and Wavelet. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_74

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  • DOI: https://doi.org/10.1007/978-3-540-87734-9_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87733-2

  • Online ISBN: 978-3-540-87734-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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