Skip to main content
SpringerLink
Log in

A Block-Adaptive Subspace Method Using Oblique Projections for Blind Separation of Convolutive Mixtures

  • Conference paper
Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

Included in the following conference series:

Abstract

This paper presents a block-adaptive subspace algorithm via oblique projection for blind source separation (BSS) problem of convolutive mixtures. In the proposed algorithm, the problem is reformulated into the one of instantaneous mixtures through oblique projections within one block, and then the separation matrix and other model parameters are updated by any static separation approach in a block-adaptive scheme. Compared with other work, the proposed algorithm can obtain lower computational complexity, faster convergence and higher robustness. Simulation results of modulation signals and real speech sources validate the proposed algorithm.

This work was supported by the National Natural Science Foundation of China under Grant 60375004.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cardoso, J., Souloumiac, A.: Blind Beamforming for Non Gaussian Signals. IEEProceedings- F 140, 362–370 (1993)

    Google Scholar 

  2. Hyvarinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. Wiley, New York (2001)

    Book  Google Scholar 

  3. Araki, S., Mukai, R., Makino, S., et al.: The Fundamental Limitation of Frequency Domain Blind Source Separation for Convolutive Mixtures of Speech. IEEE Trans. Speech and Audio Processing 21, 109–116 (2003)

    Article  Google Scholar 

  4. Amari, S., Douglas, S.C., Cichock, A., et al.: Multichannel Blind Deconvolution and Equalization Using the Natural Gradient. In: Proc. IEEE Workshop on Signal Processing Advance in Wireless Communications, Paris, France, pp. 101–104 (1997)

    Google Scholar 

  5. Mansour, A.: A Mutually Referenced Blind Multiuser Separation of Convolutive Mixture Algorithm. Signal Processing 81, 2253–2266 (2001)

    Article  MATH  Google Scholar 

  6. Hua, Y.B., An, S.J., Xiang, Y.: Blind Identification of FIR MIMO Channels by Decorrelating Subchannels. IEEE Trans. Signal Processing 51, 1143–1155 (2003)

    Article  MathSciNet  Google Scholar 

  7. Behrens, R.T., Scharf, L.L.: Signal Processing Applications of Oblique Projection Operators. IEEE Trans. Signal Processing 42, 1413–1424 (1994)

    Article  Google Scholar 

  8. Yu, X., Tong, L.: Joint Channel and Symbol Estimation by Oblique Projections. IEEE Trans. Signal Processing 49, 3074–3308 (2001)

    Article  Google Scholar 

  9. Peng, C.Y.: Research on Oblique Projectors and Their Applications in Multi-user Detection and Blind Source Separation. Master Thesis, Tsinghua University (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Laboratory of Information Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China

    Chunyi Peng, Xianda Zhang & Qutang Cai

Authors
  1. Chunyi Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xianda Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qutang Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Peng, C., Zhang, X., Cai, Q. (2005). A Block-Adaptive Subspace Method Using Oblique Projections for Blind Separation of Convolutive Mixtures. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_86

Download citation

  • DOI: https://doi.org/10.1007/11427445_86

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation