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

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Foundations of Intelligent Systems (ISMIS 1999)

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

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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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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

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