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International Symposium on Methodologies for Intelligent Systems

ISMIS 1999: Foundations of Intelligent Systems pp 402–410Cite as

Modified Oja-RLS algorithm—Stochastic convergence analysis and application for image compression

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1609))

Abstract

An analysis for stochastic convergence of the modified Oja-RLS learning rule is presented. The rule is used to find Karhunen Loeve Transform. Based on this algorithm, an image compression scheme is developed by combining approximated 2D KLT transform and JPEG standard quantization and entropy coding stages.

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References

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Author information

Authors and Affiliations

  1. Department of Electronics and Information Technology, Warsaw University of Technology, Warsaw

    Władysław Skarbek, Adam Pietrowcew & Radosław Sikora

Authors
  1. Władysław Skarbek
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  2. Adam Pietrowcew
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  3. Radosław Sikora
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Editor information

Zbigniew W. Raś Andrzej Skowron

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© 1999 Springer-Verlag Berlin Heidelberg

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Skarbek, W., Pietrowcew, A., Sikora, R. (1999). Modified Oja-RLS algorithm—Stochastic convergence analysis and application for image compression. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1999. Lecture Notes in Computer Science, vol 1609. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095127

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  • DOI: https://doi.org/10.1007/BFb0095127

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65965-5

  • Online ISBN: 978-3-540-48828-6

  • eBook Packages: Springer Book Archive

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