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This paper is concerned with the analysis of convergent sequential and parallel overlapping domain decomposition methods for the minimization of functionals formed by a discrepancy term with respect to data and a total variation constraint.…

Numerical Analysis · Mathematics 2009-05-15 Massimo Fornasier , Andreas Langer , Carola-Bibiane Schönlieb

Following the Unlimited Sampling strategy to alleviate the omnipresent dynamic range barrier, we study the problem of recovering a bandlimited signal from point-wise modulo samples, aiming to connect theoretical guarantees with hardware…

Information Theory · Computer Science 2022-04-06 Ayush Bhandari , Felix Krahmer , Thomas Poskitt

We study the problem of recovering an unknown compactly-supported multivariate function from samples of its Fourier transform that are acquired nonuniformly, i.e. not necessarily on a uniform Cartesian grid. Reconstruction problems of this…

Numerical Analysis · Mathematics 2022-05-04 Ben Adcock , Milana Gataric , José Luis Romero

Reconstructing continuous signals from a small number of discrete samples is a fundamental problem across science and engineering. In practice, we are often interested in signals with 'simple' Fourier structure, such as bandlimited,…

Data Structures and Algorithms · Computer Science 2018-12-24 Haim Avron , Michael Kapralov , Cameron Musco , Christopher Musco , Ameya Velingker , Amir Zandieh

When sampling multiple signals, the correlation between the signals can be exploited to reduce the overall number of samples. In this paper, we study the sampling theory of multiple correlated signals, using correlation to sample them at…

Signal Processing · Electrical Eng. & Systems 2022-10-11 Zhongyi Ni , Feng Ji , Hang Sheng , Hui Feng , Bo Hu

Instead of sampling a function at a single point, average sampling takes the weighted sum of function values around the point. Such a sampling strategy is more practical and more stable. In this note, we present an explicit method with an…

Information Theory · Computer Science 2014-12-23 Wenjian Chen , Haizhang Zhang

Optimal sampling of non band-limited functions is an issue of great importance that has attracted considerable attention. We propose to tackle this problem through the use of a frequency warping: First, by a nonlinear shrinking of…

Classical Analysis and ODEs · Mathematics 2017-03-07 Stefan Lafon , Jacques Lévy Véhel , Jacques Peyrière

This paper concerns the inverse source scattering problems of recovering random sources for acoustic and elastic waves. The underlying sources are assumed to be random functions driven by an additive white noise. The inversion process aims…

Numerical Analysis · Mathematics 2024-12-10 Yan Chang , Yukun Guo , Zhipeng Yang , Yue Zhao

This paper investigates inverse source problems for time-dependent electromagnetic waves governed by Maxwell's equations. After applying the Fourier transform with respect to time, the problem leads to a frequency-domain electromagnetic…

Numerical Analysis · Mathematics 2026-03-11 Fenglin Sun , Hongxia Guo

The aim of this paper is to solve an important inverse source problem which arises from the well-known inverse scattering problem. We propose to truncate the Fourier series of the solution to the governing equation with respect to a special…

Numerical Analysis · Mathematics 2022-10-18 Loc H. Nguyen , Huong T. Vu

In this paper we study the problem of computing wavelet coefficients of compactly supported functions from their Fourier samples. For this, we use the recently introduced framework of generalized sampling. Our first result demonstrates that…

Numerical Analysis · Mathematics 2013-05-14 Ben Adcock , Anders C. Hansen , Clarice Poon

The recovery of bandlimited signals with high dynamic range is a hot issue in sampling research. The unlimited sampling theory expands the recordable range of traditional analog-to-digital converters (ADCs) arbitrarily, and the signal is…

Signal Processing · Electrical Eng. & Systems 2023-02-20 Hui Zhao , Bing-Zhao Li

The machine learning random Fourier feature method for data in high dimension is computationally and theoretically attractive since the optimization is based on a convex standard least squares problem and independent sampling of Fourier…

Numerical Analysis · Mathematics 2026-05-19 Xin Huang , Aku Kammonen , Anamika Pandey , Mattias Sandberg , Erik von Schwerin , Anders Szepessy , Raúl Tempone

This paper considers the use of the anisotropic total variation seminorm to recover a two dimensional vector $x\in \mathbb{C}^{N\times N}$ from its partial Fourier coefficients, sampled along Cartesian lines. We prove that if $(x_{k,j} -…

Information Theory · Computer Science 2016-02-09 Clarice Poon

In this paper we study the general reconstruction of a compactly supported function from its Fourier coefficients using compactly supported shearlet systems. We assume that only finitely many Fourier samples of the function are accessible…

Functional Analysis · Mathematics 2015-07-31 Jackie Ma

We propose a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory. We show that perfect recovery is possible for graph signals bandlimited…

Information Theory · Computer Science 2016-11-15 Siheng Chen , Rohan Varma , Aliaksei Sandryhaila , Jelena Kovačević

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 is concerned with a direct sampling method for imaging the support of a frequency-dependent source term embedded in a homogeneous and isotropic medium. The source term is given by the Fourier transform of a time-dependent source…

Numerical Analysis · Mathematics 2022-12-12 Hongxia Guo , Guanghui Hu , Mengjie Zhao

Sampling theory in fractional Fourier Transform (FrFT) domain has been studied extensively in the last decades. This interest stems from the ability of the FrFT to generalize the traditional Fourier Transform, broadening the traditional…

Information Theory · Computer Science 2024-04-30 Václav Pavlíček , Ayush Bhandari

Super-resolution is the problem of recovering a superposition of point sources using bandlimited measurements, which may be corrupted with noise. This signal processing problem arises in numerous imaging problems, ranging from astronomy to…

Machine Learning · Computer Science 2015-09-29 Qingqing Huang , Sham M. Kakade
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