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International Conference on Independent Component Analysis and Signal Separation

ICA 2006: Independent Component Analysis and Blind Signal Separation pp 270–277Cite as

Minimum Support ICA Using Order Statistics. Part II: Performance Analysis

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

Abstract

Linear instantaneous independent component analysis (ICA) is a well-known problem, for which efficient algorithms like FastICA and JADE have been developed. Nevertheless, the development of new contrasts and optimization procedures is still needed, e.g. to improve the separation performances in specific cases. For example, algorithms may exploit prior information, such as the sparseness or the non-negativity of the sources. In this paper, we show that support-width minimization-based ICA algorithms may outperform other well-known ICA methods when extracting bounded sources. The output supports are estimated using symmetric differences of order statistics.

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References

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Author information

Authors and Affiliations

  1. Machine Learning Group, Université catholique de Louvain, Place du Levant, 3, 1380, Louvain-la-Neuve, Belgium

    Frédéric Vrins & Michel Verleysen

Authors
  1. Frédéric Vrins
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  2. Michel Verleysen
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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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Vrins, F., Verleysen, M. (2006). Minimum Support ICA Using Order Statistics. Part II: Performance Analysis. 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_34

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  • DOI: https://doi.org/10.1007/11679363_34

  • 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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