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Titlebook: Wavelets, Approximation, and Statistical Applications; Wolfgang Härdle,Gerard Kerkyacharian,Alexander Tsy Book 1998 Springer-Verlag New Yo

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Wavelets and Besov Spaces,ch more general tool in describing the smoothness properties of functions. We show that Besov spaces admit a characterization in terms of wavelet coefficients, which is not the case for Sobolev spaces. Thus the Besov spaces are intrinsically connected to the analysis of curves via wavelet techniques
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Wavelet thresholding and adaptation,d generalizations of soft and hard thresholding. Then we develop the notion of adaptive estimators and present the results about adaptivity of wavelet thresholding for density estimation problems. Finally, we consider the data-driven methods of selecting the wavelet basis, the threshold value and th
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Wavelets and Approximation,v spaces and show that it has an intrinsic relation to wavelet expansions. The presentation in this chapter and in Chapter 9 is more formal than in the previous ones. It is designed for the mathematically oriented reader who is interested in a deeper theoretical insight into the properties of wavelet bases.
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Wavelets and Approximation,v spaces and show that it has an intrinsic relation to wavelet expansions. The presentation in this chapter and in Chapter 9 is more formal than in the previous ones. It is designed for the mathematically oriented reader who is interested in a deeper theoretical insight into the properties of wavelet bases.
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