Resolution of the Wavefront Set Using General Continuous Wavelet Transforms

Resolution of the Wavefront Set Using General Continuous Wavelet Transforms
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使用一般连续小波变换的波前集分辨率

DOI:
10.1007/s00041-015-9445-7
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发表时间:
2016
影响因子:
1.2
通讯作者:
Felix Voigtlaender
Felix Voigtlaender
中科院分区:
数学3区
文献类型:
--
作者:
Jonathan Fell;Hartmut Führ;Felix Voigtlaender

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我们考虑的问题,其连续小波变换,其中后者是相对于一个适当选择的伸缩组定义的tempered distributionin的波前集的特征。在本文中,我们开发了一个全面的和统一的方法,允许建立表征的波前集的快速系数衰减,为各种各样的膨胀组。为此,我们引入了群PH的对偶作用的两个技术条件,称为微局部可容许性和(弱)锥逼近性质。从本质上讲,微局部容许性建立了一个系统之间的关系,在一个小波尺度膨胀一边,和矩阵范数的另一边。(弱)锥逼近性质描述了小波系统使其频率侧局部化适应任意频率锥的能力。微局部容许性和弱锥近似性质一起允许使用多个小波来表征波前集中的点。用较强的锥近似代替弱锥近似,得到了单小波特征。我们说明了我们的研究结果的范围,讨论在任何维度的相似性,对角和剪切膨胀组,我们验证了相关的条件。因此,相似性和对角群可以用于多个小波表征,而对于剪切波群,单个小波就足够了。特别是,剪切特征(以前只建立)在任意尺寸。
We consider the problem of characterizing the wavefront set of a tempered distributionin terms of its continuous wavelet transform, where the latter is defined with respect to a suitably chosen dilation group. In this paper we develop a comprehensive and unified approach that allows to establish characterizations of the wavefront set in terms of rapid coefficient decay, for a large variety of dilation groups. For this purpose, we introduce two technical conditions on the dual action of the groupH, calledmicrolocal admissibilityand (weak)cone approximation property. Essentially, microlocal admissibility sets up a systematic relationship between the scales in a wavelet dilated byon one side, and the matrix norm ofhon the other side. The (weak) cone approximation property describes the ability of the wavelet system to adapt its frequency-side localization to arbitrary frequency cones. Together, microlocal admissibility and the weak cone approximation property allow the characterization of points in the wavefront set using multiple wavelets. Replacing the weak cone approximation by its stronger counterpart gives rise to single wavelet characterizations. We illustrate the scope of our results by discussing—in any dimension—the similitude, diagonal and shearlet dilation groups, for which we verify the pertinent conditions. As a result, similitude and diagonal groups can be employed for multiple wavelet characterizations, whereas for the shearlet groups a single wavelet suffices. In particular, the shearlet characterization (previously only established for) holds in arbitrary dimensions.
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