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Eigenvector Algorithms with Reference Signals for Frequency Domain BSS

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Independent Component Analysis and Blind Signal Separation (ICA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3889))

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Abstract

This paper describes blind source separation (BSS) problems in the frequency domain using an eigenvector algorithm (EVA) with reference signals. The proposed EVA has such an attractive feature that all source signals are separated simultaneously from their mixtures. This is an advantage against the methods using deflation process (e.g., super-exponential method), because those methods sometimes do not work so as to converge to desired solutions, due to deflation failure. Computer simulation demonstrates the validity of the proposed EVA.

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References

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Author information

Authors and Affiliations

  1. Graduate School of Information Engineering, Nagoya University, Furo-cho Chikusa-ku, Nagoya, 464-8603, Japan

    Masanori Ito & Noboru Ohnishi

  2. Advanced Industrial Science and Technology, Tsukuba, Japan

    Mitsuru Kawamoto

  3. Bio-mimetic Control Research Center, RIKEN, Nagoya, Japan

    Mitsuru Kawamoto

  4. Department of Electronic and Control Systems Engineering, Shimane University, Matsue, Japan

    Yujiro Inouye

Authors
  1. Masanori Ito
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  2. Mitsuru Kawamoto
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  3. Noboru Ohnishi
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  4. Yujiro Inouye
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Editor information

Editors and Affiliations

  1. Siemens Corporate Research, 755 College Road East, 08540, Princeton, NJ, USA

    Justinian Rosca

  2. Department of CSEE, Oregon Health and Science University, Portland, Oregon, USA

    Deniz Erdogmus

  3. Dep. of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, USA

    José C. Príncipe

  4. McMaster University, 1280 Main Street West, L8S 4K1, Hamilton, Ontario, Canada

    Simon Haykin

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© 2006 Springer-Verlag Berlin Heidelberg

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Ito, M., Kawamoto, M., Ohnishi, N., Inouye, Y. (2006). Eigenvector Algorithms with Reference Signals for Frequency Domain BSS. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_16

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  • DOI: https://doi.org/10.1007/11679363_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32630-4

  • Online ISBN: 978-3-540-32631-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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