论文标题
从帧系统的扰动中,在索博莱夫空间中的非均匀采样和近似
Nonuniform sampling and approximation in Sobolev space from the perturbation of framelet system
论文作者
论文摘要
sobolev space $ h^q(\ mathbb {r}^{d})$,其中$ς> d/2 $是一个重要的功能空间,在各个研究领域中都有许多应用。归因于测量仪器的惯性,在抽样理论中是可取的,可以通过其非均匀采样来恢复函数。在本文中,基于Sobolev太空对的双帧系统$(h^{s}(\ Mathbb {r}^{d}),h^{ - s}(\ Mathbb {r}^{d}))$,其中$ d/2 <s <s <s <见,我们调查了所有构建问题的问题$ h^q(\ mathbb {r}^{d})$ by norriber采样。我们首先在$(h^{s}(\ Mathbb {r}^{d}),h^{ - s}(\ Mathbb {r}^{d}))$中建立Framelet系列的收敛速率,然后构建在整个空间上的framelet近似运算师$ h^um^$ {我们检查了相对于移位参数的扰动的帧近似算子的稳定性特性,并获得了用于扰动误差的估计值。我们的结果表明,在$ d/2 <s <q $的条件下,近似操作员可转移扰动。由sobolev空间中的非均匀采样和近似的一些最新工作(例如[20])的动机,我们不需要扰动序列以$ \ ell^α(\ Mathbb {z}^{d})$中的$ \ ell^α(\ ell^α(\ ell)中。我们的结果使我们能够通过nonristion sampling在$ h^ς(\ mathbb {r}^{d})中建立每个函数的近似值。特别是,近似误差对样本的抖动是可靠的。
The Sobolev space $H^ς(\mathbb{R}^{d})$, where $ς> d/2$, is an important function space that has many applications in various areas of research. Attributed to the inertia of a measurement instrument, it is desirable in sampling theory to recover a function by its nonuniform sampling. In the present paper, based on dual framelet systems for the Sobolev space pair $(H^{s}(\mathbb{R}^{d}), H^{-s}(\mathbb{R}^{d}))$, where $d/2<s<ς$, we investigate the problem of constructing the approximations to all the functions in $H^ς(\mathbb{R}^{d})$ by nonuniform sampling. We first establish the convergence rate of the framelet series in $(H^{s}(\mathbb{R}^{d}), H^{-s}(\mathbb{R}^{d}))$, and then construct the framelet approximation operator that acts on the entire space $H^ς(\mathbb{R}^{d})$. We examine the stability property for the framelet approximation operator with respect to the perturbations of shift parameters, and obtain an estimate bound for the perturbation error. Our result shows that under the condition $d/2<s<ς$, the approximation operator is robust to shift perturbations. Motivated by some recent work on nonuniform sampling and approximation in Sobolev space (e.g., [20]), we don't require the perturbation sequence to be in $\ell^α(\mathbb{Z}^{d})$. Our results allow us to establish the approximation for every function in $H^ς(\mathbb{R}^{d})$ by nonuniform sampling. In particular, the approximation error is robust to the jittering of the samples.