Reconstruction of Sampled Signals with Fractal Functions

This paper proposes a procedure to build a fractal model for real sampled signals like financial series, climatic data, bioelectric recordings, etc. The mapping constructed owns in general a rich geometric structure. In a first step, the method provides a truncate Chebyshev approximant which performs a low-pass filtering of the signal, displaying in this way the leading cycles of the phenomenon observed. In the second, the polynomial is transformed in a fractal object. The Lipschitz properties of the original signal guarantee a good approximation of the represented variable, whenever the sampling frequency is high enough.     

傅里叶变换与处处连续无处可微函数

本文介绍如何在数学分析课程中引入傅里叶变换以及利用傅里叶变换说明魏尔斯特拉斯函数的无处可微性.     

On the Windowed Fourier Transform and Wavelet Transform of Almost Periodic Functions

We present the windowed Fourier transform and wavelet transform as tools for analyzing persistent signals, such as bounded power signals and almost periodic functions. We establish the analogous Parseval-type identities. We consider discretized versions of these transforms and construct generalized frame decompositions. Finally, we bring out some relations with shift-invariant operators and linear systems.     

Hardy's Theorem and the Short-Time Fourier Transform of Schwartz Functions

The Schwartz space of rapidly decaying test functions is characterizedby the decay of the short-time Fourier transform or cross-Wignerdistribution. Then a version of Hardy's theorem is proved forthe short-time Fourier transform and for the Wigner distribution.     

On the Fast Fourier Transform Inversion of Probability Generating Functions

The fast Fourier transform can be used to invert z transforms(including probability generating functions), but this applicationhas received little attention or use. This correspondence makesa case for the FFT as a standard numerical tool in queuing andother statistical analyses in order to obtain probability densityfunctions quickly and easily. Round-off and aliasing errorsare discussed briefly for the queuing analyst without a signalprocessing background. Several variations are described whichextend the accuracy and the utility of the method.     

基于分数阶Fourier变换的尺度函数的刻画

针对分数阶Fourier变换在信号处理中应用的广泛性,引入了分数阶尺度函数与分数阶小波变换的概念.运用分数阶Fourier变换与时频分析方法研究了分数阶多分辨分析与尺度函数的构造方法,刻画分数阶尺度函数的特征.得到分数阶尺度函数存在的充要条件.     

伸缩因子为s的尺度函数傅里叶变换的支集

主要构造出了一类sd-集但非Wsd-集．同时,我们使用一种新方法,推广了一些已知的结果．基于这些结果,系统地揭示了sd-尺度函数的傅里叶变换的支集与闭球的关系．     

A “Fourier Transform” for Multiplicative Functions on Non-Crossing Partitions

We describe the structure of the group of normalized multiplicative functions on lattices of non-crossing partitions. As an application, we give a combinatorial proof of a theorem of D. Voiculescu concerning the multiplication of free random variables     

Randol Maximal Functions and the Integrability of the Fourier Transform of Measures

Mathematical Notes - Estimates of the Fourier transform of charges (measures) concentrated on smooth hypersurfaces are considered. Following M. Sugumoto, three classes of smooth hypersurfaces are...     

Numerical Approximation of Probability Mass Functions via the Inverse Discrete Fourier Transform

First passage distributions of semi-Markov processes are of interest in fields such as reliability, survival analysis, and many others. Finding or computing first passage distributions is, in general, quite challenging. We take the approach of using characteristic functions (or Fourier transforms) and inverting them to numerically calculate the first passage distribution. Numerical inversion of characteristic functions can be unstable for a general probability measure. However, we show they can be quickly and accurately calculated using the inverse discrete Fourier transform for lattice distributions. Using the fast Fourier transform algorithm these computations can be extremely fast. In addition to the speed of this approach, we are able to prove a few useful bounds for the numerical inversion error of the characteristic functions. These error bounds rely on the existence of a first or second moment of the distribution, or on an eventual monotonicity condition. We demonstrate these techniques with two examples.     

Singularities of the Radon Transform of a Class of Piecewise Smooth Functions in R2

The Radon transform is the mathematical foundation of Computerized Tomography[1](CT).Its important applications includes medical CT,noninvasive test and etc.If one is specially interested in the places at which the image function changed largely such as the interfaces of two different tissues,tissue and ill tissue and the interfaces of two difierent matters,and want to reconstruct the outlines of the interfaces,one should reconstruct the singularities of the image function.The exact inversion of the Radon transform is valid only for smooth function[2].The singularity places of the reconstructed function should be studied specially.The research includes the propagation and inversion of singularity of the Radon transform.If one use convolutionbackprojection method to reconstruct the image function,the reconstructed function become blurring at the singularity places of the original function.M.Jiang and etc[3]developed a blind deconvolution method deblurring reconstructed image.By[4]and following research,we see that one can use a neighborhood data of the singularities of the Radon transform to inverse the singularity of the Radon transform,and therefore the reconstruction is available for some incomplete data reconstructions.     

SL（2,R）上的球型函数与Fourier变换

该文中，我们主要利用对Lie群G＝SL（2，R）上球型函数的一些性质的讨论，给出了G上Fourier变换的一个重要的性质．即对每个γ∈G，存在函数f∈Cc（G），使得f（γ）≠0．     

The Fourier Transform of Functions Satisfying the Lipschitz Condition on Rank 1 Symmetric Spaces

We prove an analog of the classical Titchmarsh theorem on the image under the Fourier transform of a set of functions satisfying the Lipschitz condition in L² for functions on noncompact rank 1 Riemannian symmetric spaces.     

A Theory of Super-Resolution from Short-Time Fourier Transform Measurements

While spike trains are obviously not band-limited, the theory of super-resolution tells us that perfect recovery of unknown spike locations and weights from low-pass Fourier transform measurements is possible provided that the minimum spacing, \(\Delta \), between spikes is not too small. Specifically, for a measurement cutoff frequency of \(f_c\), Donoho (SIAM J Math Anal 23(5):1303–1331, 1992) showed that exact recovery is possible if the spikes (on \(\mathbb {R}\)) lie on a lattice and \(\Delta > 1/f_c\), but does not specify a corresponding recovery method. Candès and Fernandez-Granda (Commun Pure Appl Math 67(6):906–956, 2014; Inform Inference 5(3):251–303, 2016) provide a convex programming method for the recovery of periodic spike trains (i.e., spike trains on the torus \(\mathbb {T}\)), which succeeds provably if \(\Delta > 2/f_c\) and \(f_c \ge 128\) or if \(\Delta > 1.26/f_c\) and \(f_c \ge 10^3\), and does not need the spikes within the fundamental period to lie on a lattice. In this paper, we develop a theory of super-resolution from short-time Fourier transform (STFT) measurements. Specifically, we present a recovery method similar in spirit to the one in Candès and Fernandez-Granda (2014) for pure Fourier measurements. For a STFT Gaussian window function of width \(\sigma = 1/(4f_c)\) this method succeeds provably if \(\Delta > 1/f_c\), without restrictions on \(f_c\). Our theory is based on a measure-theoretic formulation of the recovery problem, which leads to considerable generality in the sense of the results being grid-free and applying to spike trains on both \(\mathbb {R}\) and \(\mathbb {T}\). The case of spike trains on \(\mathbb {R}\) comes with significant technical challenges. For recovery of spike trains on \(\mathbb {T}\) we prove that the correct solution can be approximated—in weak-* topology—by solving a sequence of finite-dimensional convex programming problems.     

傅立叶变换与小波变换的比较教学

本文针对小波变换教学中小流变换概念理解困难的问题，提出了一种比较教学方法，通过分析小波变换与傅立叶变换之间的联系，并从四个方面进行对比，清楚地描述了小波变换的本质，从而对加深对小波变换的理解。     

Reconstruction of Band-Limited Functions from Local Averages

In this paper, we show that every band-limited function can be reconstructed by its local averages near certain points. We give the optimal upper bounds for the support length of averaging functions with respect to both regular and irregular sampling points. Our results improve an earlier result by Gröchenig.     

Reconstruction of Convex Bodies from Brightness Functions

   Abstract. Algorithms are given for reconstructing an approximation to an unknown convex body from finitely many values of its brightness function, the function giving the volumes of its projections onto hyperplanes. One of these algorithms constructs a convex polytope with less than a prescribed number of facets, while the others do not restrict the number of facets. Convergence of the polytopes to the body is proved under certain essential assumptions including origin symmetry of the body. Also described is an oracle-polynomial-time algorithm for reconstructing an approximation to an origin-symmetric rational convex polytope of fixed and full dimension that is only accessible via its brightness function. Some of the algorithms have been implemented, and sample reconstructions are provided.     

Reconstruction of Convex Bodies from Brightness Functions

Abstract. Algorithms are given for reconstructing an approximation to an unknown convex body from finitely many values of its brightness function, the function giving the volumes of its projections onto hyperplanes. One of these algorithms constructs a convex polytope with less than a prescribed number of facets, while the others do not restrict the number of facets. Convergence of the polytopes to the body is proved under certain essential assumptions including origin symmetry of the body. Also described is an oracle-polynomial-time algorithm for reconstructing an approximation to an origin-symmetric rational convex polytope of fixed and full dimension that is only accessible via its brightness function. Some of the algorithms have been implemented, and sample reconstructions are provided.