469 research outputs found
Fast directional continuous spherical wavelet transform algorithms
We describe the construction of a spherical wavelet analysis through the
inverse stereographic projection of the Euclidean planar wavelet framework,
introduced originally by Antoine and Vandergheynst and developed further by
Wiaux et al. Fast algorithms for performing the directional continuous wavelet
analysis on the unit sphere are presented. The fast directional algorithm,
based on the fast spherical convolution algorithm developed by Wandelt and
Gorski, provides a saving of O(sqrt(Npix)) over a direct quadrature
implementation for Npix pixels on the sphere, and allows one to perform a
directional spherical wavelet analysis of a 10^6 pixel map on a personal
computer.Comment: 10 pages, 3 figures, replaced to match version accepted by IEEE
Trans. Sig. Pro
The Continuous Wavelet Transform: A Primer
Wavelet analysis is becoming more popular in the Economics discipline. Until recently, most works have made use of tools associated with the Discrete Wavelet Transform. However, after 2005, there has been a growing body of work in Economics and Finance that makes use of the Continuous Wavelet Transform tools. In this article, we give a self-contained summary on the most relevant theoretical results associated with the Continuous Wavelet Transform, the Cross-Wavelet Transform, the Wavelet Coherency and the Wavelet Phase-Difference. We describe how the transforms are usually implemented in practice and provide some examples. We also introduce the Economists to a new class of analytic wavelets, the Generalized Morse Wavelets, which have some desirable properties and provide an alternative to the Morlet Wavelet. Finally, we provide a user friendly toolbox which will allow any researcher to replicate our results and to use it in his/her own research.Economic cycles; ContinuousWavelet Transform, Cross-Wavelet Transform, Wavelet Coherency, Wavelet Phase-Difference; The Great Moderation.
The continuous wavelet transform: a primer
Wavelet analysis is becoming more popular in the Economics discipline. Until recently, most works have made use of tools associated with the Discrete Wavelet Transform. However, after 2005, there has been a growing body of work in Economics and Finance that makes use of the Continuous Wavelet Transform tools. In this article, we give a self-contained summary on the most relevant theoretical results associated with the Continuous Wavelet Transform, the Cross-Wavelet Transform, the Wavelet Coherency and the Wavelet Phase-Difference. We describe how the transforms are usually implemented in practice and provide some examples. We also introduce the Economists to a new class of analytic wavelets, the Generalized Morse Wavelets, which have some desirable properties and provide an alternative to the Morlet Wavelet. Finally, we provide a user friendly toolbox which will allow any researcher to replicate our results and to use it in his/her own research.Fundação para a Ciência e a Tecnologia (FCT) - Programa Operacional Ciência e Inovação 2010 (POCI 2010)Fundo Europeu de Desenvolvimento Regional (FEDER
Tensor network and (-adic) AdS/CFT
We use the tensor network living on the Bruhat-Tits tree to give a concrete
realization of the recently proposed -adic AdS/CFT correspondence (a
holographic duality based on the -adic number field ). Instead
of assuming the -adic AdS/CFT correspondence, we show how important features
of AdS/CFT such as the bulk operator reconstruction and the holographic
computation of boundary correlators are automatically implemented in this
tensor network.Comment: 59 pages, 18 figures; v3: improved presentation, added figures and
reference
The S-Transform From a Wavelet Point of View
Abstract—The -transform is becoming popular for time-frequency
analysis and data-adaptive filtering thanks to its simplicity.
While this transform works well in the continuous domain, its discrete
version may fail to achieve accurate results. This paper compares
and contrasts this transform with the better known continuous
wavelet transform, and defines a relation between both. This
connection allows a better understanding of the -transform, and
makes it possible to employ the wavelet reconstruction formula as
a new inverse -transform and to propose several methods to solve
some of the main limitations of the discrete -transform, such as
its restriction to linear frequency sampling.This work was supported by the projects SigSensual
ref. CTM2004-04510-C03-02 and NEAREST CE-037110. The work of
M. Schimmel was supported through the Ramon y Cajal and the Consolider-Ingenio
2010 Nr. CSD2006-00041 program.Peer reviewe
- …