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Sawin recently gave an axiomatic characterization of multiple Dirichlet series over the function field $\mathbb{F}_{q}(T)$ and proved their existence by exhibiting the coefficients as trace functions of specific perverse sheaves. However,…

Number Theory · Mathematics 2025-11-20 Matthew Hase-Liu

We study here a sequence of secondary measures, so called because the set of secondary polynomials on a given term become orthogonal for the next measure. The main result is a formula making explicit the density of any term of the sequence,…

Classical Analysis and ODEs · Mathematics 2011-04-26 Roland Groux

We prove the basic trigonometric Korovkin approximation theorem for fuzzy valued functions of two variables and verify the approximation by the help of fuzzy modulus of continuity. Also, we introduce double level Fourier series of fuzzy…

General Mathematics · Mathematics 2021-10-01 Enes Yavuz

Positive time varying frequency representation for transient signals has been a hearty desire of signal analysts due to its theoretical and practical importance. During approximately the last two decades there has formulated a signal…

Complex Variables · Mathematics 2018-05-17 Tao Qian

A Fourier-type integral representation for Bessel's function of the first kind and complex order is obtained by using the Gegenbuaer extension of Poisson's integral representation for the Bessel function along with a trigonometric integral…

Classical Analysis and ODEs · Mathematics 2017-09-01 Enrico De Micheli

The changes in brightness of an astronomical source as a function of time are key probes into that source's physics. Periodic and quasi-periodic signals are indicators of fundamental time (and length) scales in the system, while stochastic…

Instrumentation and Methods for Astrophysics · Physics 2023-08-08 Matteo Bachetti , Daniela Huppenkothen

We present a general method for decomposing non-unitary operators into a linear combination of unitary operators, where the approximation error decays exponentially. The decomposition is based on a smooth periodic extension of the identity…

Quantum Physics · Physics 2026-01-27 Peter Brearley , Thomas Howarth

This paper introduces a weighted generalized inverse framework for Fourier extensions, designed to suppress spurious oscillations in the extended region while maintaining high approximation accuracy on the original interval. By formulating…

Numerical Analysis · Mathematics 2026-01-13 Zhenyu Zhao , Yanfei Wang , Anatoly G. Yagola , Xusheng Li

Decomposition theorems in classical Fourier analysis enable us to express a bounded function in terms of few linear phases with large Fourier coefficients plus a part that is pseudorandom with respect to linear phases. The Goldreich-Levin…

Data Structures and Algorithms · Computer Science 2019-06-14 Madhur Tulsiani , Julia Wolf

Fourier decay of fractal measures on surfaces plays an important role in geometric measure theory and partial differential equations. In this paper, we study the quadratic surfaces of high co-dimensions. Unlike the case of co-dimension 1,…

Classical Analysis and ODEs · Mathematics 2024-02-20 Zhenbin Cao , Changxing Miao , Zijian Wang

Given values of a piecewise smooth function $f$ on a square grid within a domain $\Omega$, we look for a piecewise adaptive approximation to $f$. Standard approximation techniques achieve reduced approximation orders near the boundary of…

Numerical Analysis · Mathematics 2020-12-04 Sergio Amat , David Levin , Juan Ruiz-Álvarez

In this paper a sublinear time algorithm is presented for the reconstruction of functions that can be represented by just few out of a potentially large candidate set of Fourier basis functions in high spatial dimensions, a so-called…

Numerical Analysis · Mathematics 2020-06-24 Lutz Kämmerer , Felix Krahmer , Toni Volkmer

The Fourier transform of the indicator function of arbitrary polygons and polyhedra is computed for complex wavevectors. Using the divergence theorem and Stokes' theorem, closed expressions are obtained. Apparent singularities, all…

Mathematical Physics · Physics 2021-06-01 Joachim Wuttke

When Fourier series are employed to solve partial differential equations, low-pass filters can be used to regularize divergent series that may appear. In this paper we show that the linear low-pass filters defined in a previous paper can be…

Complex Variables · Mathematics 2015-03-25 Jorge L. deLyra

The Deep Fourier Residual (DFR) method is a specific type of variational physics-informed neural networks (VPINNs). It provides a robust neural network-based solution to partial differential equations (PDEs). The DFR strategy is based on…

Numerical Analysis · Mathematics 2024-01-11 Jamie M. Taylor , Manuela Bastidas , Victor M. Calo , David Pardo

In this paper we present a Fourier feature based deep domain decomposition method (F-D3M) for partial differential equations (PDEs). Currently, deep neural network based methods are actively developed for solving PDEs, but their efficiency…

Numerical Analysis · Mathematics 2022-05-05 Sen Li , Yingzhi Xia , Yu Liu , Qifeng Liao

We introduce a method to recover a continuous domain representation of a piecewise constant two-dimensional image from few low-pass Fourier samples. Assuming the edge set of the image is localized to the zero set of a trigonometric…

Computer Vision and Pattern Recognition · Computer Science 2016-04-25 Greg Ongie , Mathews Jacob

This paper presents some results on a well-known problem in Algebraic Signal Sampling and in other areas of applied mathematics: reconstruction of piecewise-smooth functions from their integral measurements (like moments, Fourier…

Classical Analysis and ODEs · Mathematics 2013-06-06 Dmitry Batenkov , Niv Sarig , Yosef Yomdin

The realization space of geometric constraint systems is given by the vanishing locus of polynomials corresponding to natural geometric constraints. Such geometric constraint systems arise in many real-world scenarios such as structural…

Metric Geometry · Mathematics 2026-04-14 Matthias Adrian-Himmelmann

This paper describes a novel method to approximate the polynomial coefficients of regression functions, with particular interest on multi-dimensional classification. The derivation is simple, and offers a fast, robust classification…

Machine Learning · Statistics 2012-03-27 Péter Kövesárki
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