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Titlebook: Essential Wavelets for Statistical Applications and Data Analysis; R. Todd Ogden Book 1997 Springer Science+Business Media New York 1997 E

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發(fā)表于 2025-3-23 10:30:40 | 只看該作者
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發(fā)表于 2025-3-23 15:38:20 | 只看該作者
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發(fā)表于 2025-3-23 21:04:34 | 只看該作者
Book 1997ect popular (Meyer‘s book is one of the early works written with the non- specialist in mind), the implication seems to be that such an attempt some- how cheapens or coarsens the subject. I have to disagree that popularity goes hand-in-hand with debasement. is certainly a beautiful theory underlying
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發(fā)表于 2025-3-23 22:44:59 | 只看該作者
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發(fā)表于 2025-3-24 04:22:15 | 只看該作者
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發(fā)表于 2025-3-24 08:18:14 | 只看該作者
Data Adaptive Wavelet Thresholding,gonal wavelet transform on the unit interval is used, and that the sample size is a power of two: . = 2. for some integer . > 0. When this condition is not met, the methods described herein may be adapted, using techniques described in Chapter 6.
17#
發(fā)表于 2025-3-24 14:15:12 | 只看該作者
Basic Smoothing Techniques,rnel smoothing and orthogonal series estimation. This background should provide a useful lead-in to a discussion of wavelet methods for function estimation, since standard techniques in these two areas can be modified in a straightforward manner to use wavelets.
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發(fā)表于 2025-3-24 17:33:41 | 只看該作者
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