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Wavelet Compression, Data Fitting and Approximation Based on Adaptive Composition of Lorentz-Type Thresholding and Besov-Type Non-threshold Shrinkage

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Large-Scale Scientific Computing (LSSC 2009)

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Abstract

In this study we initiate the investigation of a new advanced technique, proposed in Section 6 of [3], for generating adaptive Besov–Lorentz composite wavelet shrinkage strategies. We discuss some advantages of the Besov–Lorentz approach compared to firm thresholding.

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Dechevsky, L.T., Gundersen, J., Grip, N. (2010). Wavelet Compression, Data Fitting and Approximation Based on Adaptive Composition of Lorentz-Type Thresholding and Besov-Type Non-threshold Shrinkage. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2009. Lecture Notes in Computer Science, vol 5910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12535-5_88

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  • DOI: https://doi.org/10.1007/978-3-642-12535-5_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12534-8

  • Online ISBN: 978-3-642-12535-5

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