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Local Convergence Analysis of FastICA

  • Conference paper
Independent Component Analysis and Blind Signal Separation (ICA 2006)

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

Abstract

The FastICA algorithm can be considered as a selfmap on a manifold. It turns out that FastICA is a scalar shifted version of an algorithm recently proposed. We put these algorithms into a dynamical system framework. The local convergence properties are investigated subject to an ideal ICA model. The analysis is very similar to the wellknown case in numerical linear algebra when studying power iterations versus Rayleigh quotient iteration.

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Author information

Authors and Affiliations

  1. Department of Information Engineering, Research School of Information Sciences and Engineering, The Australian National University, Canberra, ACT, 0200, Australia

    Hao Shen & Knut Hüper

  2. Systems Engineering and Complex Systems Research Program, National ICT Australia, Canberra Research Laboratory, Locked Bag 8001, Canberra, ACT, 2612, Australia

    Hao Shen & Knut Hüper

Authors
  1. Hao Shen
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  2. Knut Hüper
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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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Shen, H., Hüper, K. (2006). Local Convergence Analysis of FastICA. 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_111

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  • DOI: https://doi.org/10.1007/11679363_111

  • 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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