Skip to main content

Optimal Joint Diagonalization of Complex Symmetric Third-Order Tensors. Application to Separation of Non Circular Signals

  • Conference paper
Independent Component Analysis and Signal Separation (ICA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4666))

Abstract

In this paper, we address the problem of blind source separation of non circular digital communication signals. A new Jacobi-like algorithm that achieves the joint diagonalization of a set of symmetric third-order tensors is proposed. The application to the separation of non-gaussian sources using fourth order cumulants is particularly investigated. Finally, computer simulations on synthetic signals show that this new algorithm improves the STOTD algorithm.

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. Cardoso, J.-F., Souloumiac, A.: Blind beamforming for non Gaussian signals. IEE Proceedings-F 140, 362–370 (1993)

    Google Scholar 

  2. Comon, P.: Independent Component Analysis, A New Concept? Signal Processing 36, 287–314 (1994)

    Article  MATH  Google Scholar 

  3. De Lathauwer, L., De Moor, B., Vanderwalle, J.: Independent Component Analysis and (Simultaneous) Third-Order Tensor Diagonalization. IEEE Transactions on Signal Processing 49, 2262–2271 (2001)

    Article  Google Scholar 

  4. Moreau, E.: A Generalization of Joint-Diagonalization Criteria for Source Separation. IEEE Transactions on Signal Processing 49, 530–541 (2001)

    Article  Google Scholar 

  5. De Lathauwer, L., De Moor, B., Vanderwalle, J.: ICA techniques for more sources than sensors. In: Proceeding of the IEEE Signal Processing Workshop on Higher-Order Statistics (HOS 1999), June 1999, Caesarea, Israel, pp. 121–124 (1999)

    Google Scholar 

  6. De Lathauwer, L., De Moor, B.: On the Blind Separation of Non-circular Sources. In: Proceeding of EUSIPCO-02, (September 2002), Toulouse, France, vol. II, pp. 99–102 (2002)

    Google Scholar 

  7. Chevalier, P.: Optimal Ttime invariant and widely linear spatial filtering for radiocommunications. In: Proc. EUSIPCO 1996, Trieste, Italy, September 1996, pp. 559–562 (1996)

    Google Scholar 

  8. Chevalier, P.: Optimal array processing for non stationary signals. In Proc. ICASSP 1996, Atlanta, pp. 2868–2871 (May 1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Mike E. Davies Christopher J. James Samer A. Abdallah Mark D Plumbley

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

De Luigi, C., Moreau, E. (2007). Optimal Joint Diagonalization of Complex Symmetric Third-Order Tensors. Application to Separation of Non Circular Signals. In: Davies, M.E., James, C.J., Abdallah, S.A., Plumbley, M.D. (eds) Independent Component Analysis and Signal Separation. ICA 2007. Lecture Notes in Computer Science, vol 4666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74494-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74494-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74493-1

  • Online ISBN: 978-3-540-74494-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics