Skip to main content

ICA Separability of Nonlinear Models with References: General Properties and Application to Heisenberg-Coupled Quantum States (Qubits)

  • 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

Relatively few results were reported about the separability of given classes of nonlinear mixtures by means of the ICA criterion. We here prove the separability of a wide class of nonlinear global (i.e. mixing + separating) models involving ”reference signals”, i.e. unmixed signals. This work therefore concerns a nonlinear extension of linear adaptive noise cancellation (ANC). We then illustrate the usefulness of our general results by applying them to a model of Heisenberg-coupled quantum states. This paper opens the way to practical ICA methods for nonlinear mixtures encountered in various applications.

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

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., Jutten, C. (eds.): Handbook of blind source separation, independent component analysis and applications. Academic Press, London (2010)

    Google Scholar 

  2. Deville, Y., Deville, A.: Maximum likelihood blind separation of two quantum states (qubits) with cylindrical-symmetry Heisenberg spin coupling. In: Proceedings of ICASSP 2008, Las Vegas, Nevada, USA, March 30 - April 4, pp. 3497–3500 (2008)

    Google Scholar 

  3. Deville, Y., Hosseini, S.: Recurrent networks for separating extractable-target nonlinear mixtures. Part I: non-blind configurations. Signal Processing 89(4), 378–393 (2009), http://dx.doi.org/10.1016/j.sigpro.2008.09.016

    Article  MATH  Google Scholar 

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

    Book  Google Scholar 

  5. Jutten, C., Karhunen, J.: Advances in Blind Source Separation (BSS) and Independent Component Analysis (ICA) for Nonlinear Mixtures. International Journal of Neural Systems 14(5), 267–292 (2004)

    Article  Google Scholar 

  6. Widrow, B., Glover, J.R., McCool, J.M., Kaunitz, J., Williams, C.S., Hearn, R.H., Zeidler, J.R., Dong, E., Goodlin, R.C.: Adaptive noise cancelling: principles and applications. Proceedings of the IEEE 63(12), 1692–1716 (1975)

    Article  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

Deville, Y. (2010). ICA Separability of Nonlinear Models with References: General Properties and Application to Heisenberg-Coupled Quantum States (Qubits). 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_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15995-4_22

  • 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