Skip to main content

Complex Blind Source Separation via Simultaneous Strong Uncorrelating Transform

  • Conference paper
Latent Variable Analysis and Signal Separation (LVA/ICA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6365))

Abstract

In this paper, we address the problem of complex blind source separation (BSS), in particular, separation of nonstationary complex signals. It is known that, under certain conditions, complex BSS can be solved effectively by the so-called Strong Uncorrelating Transform (SUT), which simultaneously diagonalizes one Hermitian positive definite and one complex symmetric matrix. Our current work generalizes SUT to simultaneously diagonalize more than two matrices. A Conjugate Gradient (CG) algorithm for computing simultaneous SUT is developed on an appropriate manifold setting of the problem, namely complex oblique projective manifold. Performance of our method, in terms of separation quality, is investigated by several numerical experiments.

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

Access this chapter

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. Comon, P.: Independent component analysis, a new concept? Signal Processing 36(3), 287–314 (1994)

    Article  MATH  Google Scholar 

  2. Eriksson, J., Koivunen, V.: Complex random vectors and ICA models: Identifiability, uniqueness, and separability. IEEE Transactions on Information Theory 52(3), 1017–1029 (2006)

    Article  MathSciNet  Google Scholar 

  3. Eriksson, J., Koivunen, V.: Complex-valued ICA using second order statistics. In: Proceedings of the IEEE-MLSP 2004, pp. 183–191 (2004)

    Google Scholar 

  4. Ollila, E., Koivunen, V.: Complex ICA using generalized uncorrelating transform. Signal Processing 89, 365–377 (2009)

    Article  MATH  Google Scholar 

  5. Cardoso, J.F.: Blind signal separation: Statistical principles. Proceedings of the IEEE 86(10), 2009–2025 (1998)

    Article  Google Scholar 

  6. Douglas, S.C., Eriksson, J., Koivunen, V.: Equivariant algorithms for estimating the strong-uncorrelating transform in complex independent component analysis. In: Rosca, J.P., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds.) ICA 2006. LNCS, vol. 3889, pp. 57–65. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  7. Pham, D.T.: Joint approximate diagonalization of positive definite Hermitian matrices. SIAM Journal on Matrix Analysis and Applications 22, 1136–1152 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  8. Neeser, F., Massey, J.: Proper complex random processes with applications to information theory. IEEE Transactions on Information Theory 39(4), 1293–1302 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  9. Spivak, M.: A Comprehensive Introduction to Differential Geometry, 3rd edn., vol. 1 - 5. Publish or Perish, Inc. (1999)

    Google Scholar 

  10. Afsari, B.: Sensitivity analysis for the problem of matrix joint diagonalization. SIAM Journal on Matrix Analysis and Applications 20, 1148–1171 (2008)

    Article  MathSciNet  Google Scholar 

  11. Kleinsteuber, M., Hüper, K.: An intrinsic CG algorithm for computing dominant subspaces. In: Proceedings of IEEE-ICASSP 2007, pp. IV1405–IV1408 (2007)

    Google Scholar 

  12. Amari, S., Cichocki, A., Yang, H.H.: A new learning algorithm for blind signal separation. In: Advances in Neural Information Processing Systems, vol. 8, pp. 757–763 (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Shen, H., Kleinsteuber, M. (2010). Complex Blind Source Separation via Simultaneous Strong Uncorrelating Transform. In: Vigneron, V., Zarzoso, V., Moreau, E., Gribonval, R., Vincent, E. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2010. Lecture Notes in Computer Science, vol 6365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15995-4_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15995-4_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15994-7

  • Online ISBN: 978-3-642-15995-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics