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Weighted average sampling is more practical and numerically more stable than sampling at single points as in the classical Shannon sampling framework. Using the frame theory, one can completely reconstruct a bandlimited function from its…

Information Theory · Computer Science 2014-07-04 Haizhang Zhang

Reconstructing a band-limited function from its finite sample data is a fundamental task in signal analysis. A Gaussian regularized Shannon sampling series has been proved to be able to achieve exponential convergence for uniform sampling.…

Signal Processing · Electrical Eng. & Systems 2022-10-10 Yunfei Yang , 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

We consider the recovery of real-valued bandlimited functions from the absolute values of their samples, possibly spaced nonuniformly. We show that such a reconstruction is always possible if the function is sampled at more than twice its…

Numerical Analysis · Mathematics 2012-01-17 Gaurav Thakur

The Shannon sampling theorem for bandlimited wide sense stationary random processes was established in 1957, which and its extensions to various random processes have been widely studied since then. However, truncation of the Shannon series…

Functional Analysis · Mathematics 2014-01-21 Wenjian Chen , Haizhang Zhang

We present an approximation scheme for functions in three dimensions, that requires only their samples on the Cartesian grid, under the assumption that the functions are sufficiently concentrated in both space and frequency. The scheme is…

Numerical Analysis · Mathematics 2022-12-16 Rami Katz , Yoel Shkolnisky

Soft extrapolation refers to the problem of recovering a function from its samples, multiplied by a fast-decaying window and perturbed by an additive noise, over an interval which is potentially larger than the essential support of the…

Numerical Analysis · Mathematics 2018-12-26 Dmitry Batenkov , Laurent Demanet , Hrushikesh N. Mhaskar

We consider the problem of random sampling for band-limited functions. When can a band-limited function $f$ be recovered from randomly chosen samples $f(x_j), j\in \mathbb{N}$? We estimate the probability that a sampling inequality of the…

Probability · Mathematics 2011-04-27 Karlheinz Gröchenig , Richard F. Bass

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

We propose a general method for optimization with semi-infinite constraints that involve a linear combination of functions, focusing on the case of the exponential function. Each function is lower and upper bounded on sub-intervals by…

Optimization and Control · Mathematics 2014-01-13 Bogdan Dumitrescu , Bogdan C. Sicleru , Florin Avram

We consider the problem of reconstructing a wide sense stationary band-limited process from its local averages taken either at the Nyquist rate or above. As a result, we obtain a sufficient condition under which average sampling expansions…

Information Theory · Computer Science 2012-11-29 Gilles Faÿ , Sinuk Kang

We introduce a numerical method for the approximation of functions which are analytic on compact intervals, except at the endpoints. This method is based on variable transforms using particular parametrized exponential and…

Numerical Analysis · Mathematics 2016-09-06 Ben Adcock , Jésus Martín-Vaquero , Mark Richardson

We give a general strategy to construct superoscillating/growing functions using an orthogonal polynomial expansion of a bandlimited function. The degree of superoscillation/growth is controlled by an anomalous expectation value of a…

Mathematical Physics · Physics 2023-11-08 Tathagata Karmakar , Andrew N. Jordan

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

The need to Fourier transform data sets with irregular sampling is shared by various domains of science. This is the case for example in astronomy or sismology. Iterative methods have been developed that allow to reach approximate…

Numerical Analysis · Mathematics 2024-01-23 Guy Perrin

Function approximation and recovery via some sampled data have long been studied in a wide array of applied mathematics and statistics fields. Analytic tools, such as the Poincar\'e inequality, have been handy for estimating the…

Numerical Analysis · Mathematics 2020-07-16 Yifan Chen , Thomas Y. Hou

Binary measurements arise naturally in a variety of statistical and engineering applications. They may be inherent to the problem---e.g., in determining the relationship between genetics and the presence or absence of a disease---or they…

Information Theory · Computer Science 2014-08-01 Richard Baraniuk , Simon Foucart , Deanna Needell , Yaniv Plan , Mary Wootters

In this paper, we investigate frames for $L_2[-\pi,\pi]^d$ consisting of exponential functions in connection to oversampling and nonuniform sampling of bandlimited functions. We derive a multidimensional nonuniform oversampling formula for…

Numerical Analysis · Mathematics 2010-09-13 Benjamin Aaron Bailey

This paper deals with some nonlinear problems which exponential and biexponential decays are involved in. A proof of the quasiconvexity of the error function in some of these problems of optimization is presented. This proof is restricted…

We consider approximation or recovery of functions based on a finite number of function evaluations. This is a well-studied problem in optimal recovery, machine learning, and numerical analysis in general, but many fundamental insights were…

Numerical Analysis · Mathematics 2026-04-07 David Krieg , Mario Ullrich
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