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International Conference on Independent Component Analysis and Signal Separation

ICA 2004: Independent Component Analysis and Blind Signal Separation pp 41–48Cite as

Optimization Issues in Noisy Gaussian ICA

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3195))

Abstract

This paper addresses the blind separation of noisy mixtures of independent sources. It discusses issues and techniques related to computing maximum likelihood estimates in Gaussian models.

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References

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Author information

Authors and Affiliations

  1. CNRS/LTCI, UMR, 5141, Paris, France

    Jean-François Cardoso

  2. CNRS/LMC-IMAG, Grenoble, France

    Dinh-Tuan Pham

Authors
  1. Jean-François Cardoso
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  2. Dinh-Tuan Pham
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Editor information

Editors and Affiliations

  1. Dept. of Architecture and Computer Technology, University of Granada, Spain

    Carlos G. Puntonet  & Alberto Prieto  & 

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© 2004 Springer-Verlag Berlin Heidelberg

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Cite this paper

Cardoso, JF., Pham, DT. (2004). Optimization Issues in Noisy Gaussian ICA. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_6

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23056-4

  • Online ISBN: 978-3-540-30110-3

  • eBook Packages: Springer Book Archive

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