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ICA by Maximizing Non-stability

  • Conference paper
Independent Component Analysis and Signal Separation (ICA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5441))

Abstract

We propose a new approach for ICA by maximizing the non-stability contrast function in this paper. This new version of ICA is motivated by the Generalized Central Limit Theorem (GCLT), an important extension of classical CLT. We demonstrate that the classical ICA based on maximization of non-Gaussianity is a special case of the new approach of ICA we introduce here which is based on maximization of non-Stability with certain constraints. To be able to quantify non-stability, we introduce a new measure of stability namely Alpha-stable negentropy. A numerical gradient ascent algorithm for the maximization of the alpha-stable negentropy with the objective of source separation is also introduced in this paper. Experiments show that ICA by maximum of non-stability performs very successfully in impulsive source separation problems.

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References

  1. Kuruoglu, E.E.: Density Parameter Estimation of Skewed alpha-Stable Distribution. IEEE transactions on signal processing 49(10), 2192–2201 (2001)

    Article  MathSciNet  Google Scholar 

  2. Nikias, C.L., Shao, M.: Signal Processing with Alpha-Stable Distributions and Applications. Wiley, New York (1995)

    Google Scholar 

  3. Samorodnitsky, G., Taqqu, M.: Stable non-Gaussian random processes. Chapman and Hall, New York (1994)

    MATH  Google Scholar 

  4. Hyvärinen, A., Oja, E.: Independent Component Analysis: Algorithms and Applications. Neural Networks 13, 411–430 (2004)

    Article  Google Scholar 

  5. Nolan, J.P.: Numerical Calculation of Stable Densities and Distribution Functions. Stochastic Models 13(4), 759–774 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  6. Hyvärinen, A.: Fast and Robust Fixed-Point Algorithms for Independent Component Analysis. IEEE Transactions on Neural Networks 10(3), 626–634 (1999)

    Article  Google Scholar 

  7. Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Chichester (2001)

    Book  Google Scholar 

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

    Article  MATH  Google Scholar 

  9. Hyvärinen, A.: Survey on Independent Component Analysis. Neural Computing Surveys 2, 94–128 (1999)

    Google Scholar 

  10. Sahmoudi, M., Abed-Meraim, K., Benidir, M.: Blind Separation of Impulsive Alpha-Stable Sources Using Minimum Dispersion Criterion. IEEE Signal Processing Letters 12(4), 281–284 (2005)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Xidian University, P.O BOX 175, No. 2 South TaiBai Road, Xi’an, 710071, China

    Baijie Wang & Junying Zhang

  2. ISTI-CNR, via G. Moruzzi 1, 56124, Pisa, Italy

    Ercan E. Kuruoglu

Authors
  1. Baijie Wang
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  2. Ercan E. Kuruoglu
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  3. Junying Zhang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Electrical Engineering, ITE 324, University of Maryland, Baltimore County, 1000 Hilltop Circle, MD 21250, Baltimore, USA

    Tülay Adali

  2. Domaine Universitaire, GIPSA-lab, BP 46, 38402, Saint Martin d’Hères Cedex, France

    Christian Jutten

  3. Departamento de Microonda e Óptica (DMO), FEEC / Unicamp, Avenida Albert Einstein 400, 13083-852, Campinas, Sao Paulo, Brazil

    João Marcos Travassos Romano

  4. Centro Tecnológico, Curso de Engenharia Elétrica, Universidade Federal do Maranhão, Avenida dos Portugueses, s/n, Bacanga, 65080-040, São Luís, MA, Brazil

    Allan Kardec Barros

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© 2009 Springer-Verlag Berlin Heidelberg

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Wang, B., Kuruoglu, E.E., Zhang, J. (2009). ICA by Maximizing Non-stability. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_23

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  • DOI: https://doi.org/10.1007/978-3-642-00599-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00598-5

  • Online ISBN: 978-3-642-00599-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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