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Operator-Like Wavelet Bases of L_2(R~d)

机译:L_2(R〜d)的类似算子的小波基

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摘要

The connection between derivative operators and wavelets is well known. Here we generalize the concept by constructing multiresolution approximations and wavelet basis functions that act like Fourier multiplier operators. This construction follows from a stochastic model: signals are tempered distributions such that the application of a whitening (differential) operator results in a realization of a sparse white noise. Using wavelets constructed from these operators, the sparsity of the white noise can be inherited by the wavelet coefficients. In this paper, we specify such wavelets in full generality and determine their properties in terms of the underlying operator.
机译:导数算子和小波之间的联系是众所周知的。在这里,我们通过构造像傅立叶乘法器算子一样的多分辨率近似和小波基函数来概括该概念。这种构造是根据随机模型得出的:信号是经过缓和的分布,因此应用白化(微分)算子会导致稀疏白噪声的实现。使用由这些算子构造的小波,白噪声的稀疏性可以由小波系数继承。在本文中,我们将全面地指定此类小波,并根据底层算子确定其属性。

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