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We introduce an algebra $\mathcal H$ consisting of difference-reflection operators and multiplication operators that can be considered as a $q=1$ analogue of Sahi's double affine Hecke algebra related to the affine root system of type…

Representation Theory · Mathematics 2007-06-13 Wolter Groenevelt

Parseval frames have particularly useful properties, and in some cases, they can be used to reconstruct signals which were analyzed by a non-Parseval frame. In this paper, we completely describe the degree to which such reconstruction is…

Functional Analysis · Mathematics 2013-10-01 G. Corach , P. Massey , M. Ruiz

Partial Fourier transforms are used to find explicit formulas for two remarkable fundamental solutions for a generalized Tricomi operator. These fundamental solutions reflect clearly the mixed type of the operator. In order to prove these…

Classical Analysis and ODEs · Mathematics 2007-05-23 J. Barros-Neto , Fernando Cardoso

In this paper, we use basic asymptotic analysis to establish some uniform asymptotic formulas for the Fourier coefficients of the inverse of Jacobi theta functions. In particular, we answer and improve some problems suggested and…

Number Theory · Mathematics 2021-03-31 Zhi-Guo Liu , Nian Hong Zhou

This paper develops a constructive numerical scheme for Fourier-Bessel approximations on disks compatible with convolutions supported on disks. We address accurate finite Fourier-Bessel transforms (FFBT) and inverse finite Fourier-Bessel…

Numerical Analysis · Mathematics 2023-11-08 Arash Ghaani Farashahi , Gregory S. Chirikjian

We prove new explicit upper bounds on the leverage scores of Fourier sparse functions under both the Gaussian and Laplace measures. In particular, we study $s$-sparse functions of the form $f(x) = \sum_{j=1}^s a_j e^{i \lambda_j x}$ for…

Data Structures and Algorithms · Computer Science 2021-07-09 Tamás Erdélyi , Cameron Musco , Christopher Musco

Periodic activation functions, often referred to as learned Fourier features have been widely demonstrated to improve sample efficiency and stability in a variety of deep RL algorithms. Potentially incompatible hypotheses have been made…

Machine Learning · Computer Science 2025-03-20 Augustine N. Mavor-Parker , Matthew J. Sargent , Caswell Barry , Lewis Griffin , Clare Lyle

We generalize the classic Fourier transform operator $\mathcal{F}_{p}$ by using the Henstock-Kurzweil integral theory. It is shown that the operator equals the $HK$-Fourier transform on a dense subspace of $\mathcal{ L}^p$, $1<p\leq 2$. In…

Classical Analysis and ODEs · Mathematics 2020-07-23 Juan H. Arredondo , M. Guadalupe Morales , Manuel Bernal G

Automatic algorithms attempt to provide approximate solutions that differ from exact solutions by no more than a user-specified error tolerance. This paper describes an automatic, adaptive algorithm for approximating the solution to a…

Numerical Analysis · Mathematics 2018-09-28 Yuhan Ding , Fred J. Hickernell , Lluís Antoni Jiménez Rugama

We show that for multivariate Freud-type weights $W_\alpha(x)=\exp(-|x|^\alpha)$, $\alpha>1$, any convex function $f$ on $R^d$ satisfying $fW_\alpha\in L_p(R^d)$ if $1\le p<\infty$, or $\lim_{|x|\to\infty}f(x)W_\alpha(x)=0$ if $p=\infty$,…

Classical Analysis and ODEs · Mathematics 2014-11-14 Oleksandr Maizlish , Andriy Prymak

Usually such area of mathematics as differential equations acts as a consumer of results given by functional analysis. This article will give an example of the reverse interaction of these two fields of knowledge. Namely, the derivation and…

Classical Analysis and ODEs · Mathematics 2026-05-14 Alexey Gorshkov

The famous Fourier theorem states that, under some restrictions, any periodic function (or real world signal) can be obtained as a sum of sinusoids, and hence, a technique exists for decomposing a signal into its sinusoidal components. From…

Numerical Analysis · Computer Science 2008-04-24 Sossio Vergara

For real symmetric positive definite matrices $A$ and $B$, we characterize when a function $f \in L^2(\mathbb{R}^d)$ satisfies \[ |f(x)| \lesssim e^{-(\frac12 - \lambda) \langle Ax, x\rangle} \quad \text{and} \quad |\widehat{f}(\xi)|…

Functional Analysis · Mathematics 2025-11-27 Lenny Neyt , Joachim Toft , Jasson Vindas

In this paper we develop elements of the global calculus of Fourier integral operators in $R^n$ under minimal decay assumptions on phases and amplitudes. We also establish global weighted Sobolev $L^2$ estimates for a class of Fourier…

Analysis of PDEs · Mathematics 2011-08-11 Michael Ruzhansky , Mitsuru Sugimoto

In this paper, we investigate the mapping properties of pseudo-differential operators with operator-valued symbols. Thanks to the smooth atomic decomposition of the operator-valued Triebel-Lizorkin spaces…

Operator Algebras · Mathematics 2018-04-11 Runlian Xia , Xiao Xiong

We prove a uniform generalized gaussian bound for the powers of a discrete convolution operator in one space dimension. Our bound is derived under the assumption that the Fourier transform of the coefficients of the convolution operator is…

Numerical Analysis · Mathematics 2021-11-23 Jean-François Coulombel , Grégory Faye

We generalize an idea of Picioroaga and Weber to construct Paseval frames of weighted exponential functions for self-affine measures.

Functional Analysis · Mathematics 2016-06-17 Dorin Ervin Dutkay , Rajitha Ranasinghe

The pointwise estimates of the deviations $\widetilde{T}_{n,A,B}^{\text{}%}f\left(\cdot \right) -\widetilde{f}(\cdot)$ and $\widetilde{T}_{n,A,B}^{% \text{}}f\left(\cdot \right) -\widetilde{f}(\cdot,\varepsilon)$ in terms of moduli of…

Analysis of PDEs · Mathematics 2014-05-19 Wlodzimierz Lenski , Bogdan Szal

We consider a topological integral transform of Bessel (concentric isospectral sets) type and Fourier (hyperplane isospectral sets) type, using the Euler characteristic as a measure. These transforms convert constructible $\zed$-valued…

Algebraic Topology · Mathematics 2015-05-20 Robert Ghrist , Michael Robinson

Frank-Wolfe methods (FW) have gained significant interest in the machine learning community due to its ability to efficiently solve large problems that admit a sparse structure (e.g. sparse vectors and low-rank matrices). However the…

Machine Learning · Statistics 2018-03-22 Edward Cheung , Yuying Li