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From Differential Equations to the Construction of New Wavelet-Like Bases

机译:从微分方程到新的小波类基的构造

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In this paper, an approach is introduced based on differential operators to construct wavelet-like basis functions. Given a differential operator L with rational transfer function, elementary building blocks are obtained that are shifted replicates of the Green's function of L. It is shown that these can be used to specify a sequence of embedded spline spaces that admit a hierarchical exponential B-spline representation. The corresponding B-splines are entirely specified by their poles and zeros; they are compactly supported, have an explicit analytical form, and generate multiresolution Riesz bases. Moreover, they satisfy generalized refinement equations with a scale-dependent filter and lead to a representation that is dense in L_(2). This allows us to specify a corresponding family of semi-orthogonal exponential spline wavelets, which provides a major extension of earlier polynomial spline constructions. These wavelets are completely characterized, and it is proven that they satisfy the following remarkable properties: 1) they are orthogonal across scales and generate Riesz bases at each resolution level; 2) they yield unconditional bases of L_(2)--either compactly supported (B-spline-type) or with exponential decay (orthogonal or dual-type); 3) they have N vanishing exponential moments, where N is the order of the differential operator; 4) they behave like multiresolution versions of the operator L from which they are derived; and 5) their order of approximation is (N - M), where N and M give the number of poles and zeros, respectively. Last but not least, the new wavelet-like decompositions are as computationally efficient as the classical ones. They are computed using an adapted version of Mallat's filter bank algorithm, where the filters depend on the decomposition level.
机译:本文介绍了一种基于微分算子的构造小波基函数的方法。给定具有有理传递函数的微分算子L,可以获得基本构造块,这些基本构造块是L的格林函数的移位副本。表明,这些构造块可用于指定允许分层指数B样条的嵌入样条空间的序列表示。相应的B样条完全由其极点和零点指定;它们得到紧凑的支持,具有明确的分析形式,并生成多分辨率Riesz基数。此外,它们满足了与比例相关的滤波器的广义优化方程,并导致在L_(2)中密集。这使我们可以指定相应的半正交指数样条小波族,从而大大简化了先前的多项式样条构造。这些小波已被完全表征,并证明它们满足以下显着特性:1)它们在各个尺度上正交,并在每个分辨率级别生成Riesz基。 2)它们产生L_(2)的无条件底数-紧支撑(B样条型)或指数衰减(正交或对偶型); 3)它们具有N个消失的指数矩,其中N是微分算子的阶数; 4)它们的行为就像从中得出它们的算子L的多分辨率版本;和5)它们的近似阶数为(N-M),其中N和M分别给出极点数和零点数。最后但并非最不重要的一点是,新的类似小波的分解在计算上与经典分解一样高效。它们是使用Mallat滤波器组算法的改编版本进行计算的,其中滤波器取决于分解级别。

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