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The probability density function (PDF) associated with a given set of samples is approximated by a piecewise-linear polynomial constructed with respect to a binning of the sample space. The kernel functions are a compactly supported basis…

Numerical Analysis · Mathematics 2020-08-04 Giacomo Capodaglio , Max Gunzburger

We prove that every nonnegative continuous real-valued function on a given compact metric space is the uniform limit of some increasing sequence of nonnegative simple functions being linear combinations of indicators of open sets; here the…

General Mathematics · Mathematics 2020-10-21 Yu-Lin Chou

We introduce an algorithm of joint approximation of a function and its first derivative by alternative orthogonal polynomials on the interval [0,1].The algorithm exhibits properties of shape preserving approximation for the function. A weak…

Numerical Analysis · Mathematics 2020-01-14 Vladimir S. Chelyshkov

A deep approximation is an approximating function defined by composing more than one layer of simple functions. We study deep approximations of functions of one variable using layers consisting of low-degree polynomials or simple conformal…

Numerical Analysis · Mathematics 2025-04-25 Kingsley Yeon

A convincing feature of least-squares finite element methods is the built-in a posteriori error estimator for any conforming discretization. In order to generalize this property to discontinuous finite element ansatz functions, this paper…

Numerical Analysis · Mathematics 2025-02-18 Philipp Bringmann

We consider approximating analytic functions on the interval $[-1,1]$ from their values at a set of $m+1$ equispaced nodes. A result of Platte, Trefethen \& Kuijlaars states that fast and stable approximation from equispaced samples is…

Numerical Analysis · Mathematics 2022-03-08 Ben Adcock , Alexei Shadrin

We propose a new method of adaptive piecewise approximation based on Sinc points for ordinary differential equations. The adaptive method is a piecewise collocation method which utilizes Poly-Sinc interpolation to reach a preset level of…

Numerical Analysis · Mathematics 2022-09-29 Omar Khalil , Hany El-Sharkawy , Maha Youssef , Gerd Baumann

The purpose of the paper is to provide a characterization of the error of the best polynomial approximation of composite functions in weighted spaces. Such a characterization is essential for the convergence analysis of numerical methods…

Numerical Analysis · Mathematics 2023-08-14 Luisa Fermo , Concetta Laurita , Maria Grazia Russo

This paper introduces first order Sobolev spaces on certain rectifiable varifolds. These complete locally convex spaces are contained in the generally nonlinear class of generalised weakly differentiable functions and share key functional…

Classical Analysis and ODEs · Mathematics 2017-05-25 Ulrich Menne

The best polynomial approximation and Chebyshev approximation are both important in numerical analysis. In tradition, the best approximation is regarded as more better than the Chebyshev approximation, because it is usually considered in…

Numerical Analysis · Mathematics 2021-11-17 Xiaolong Zhang

We present a method for constructing global analytical expressions that approximate a function over its entire range. These approximations not only mirror the original function as accurately as desired, but are purposefully created to…

High Energy Physics - Phenomenology · Physics 2024-07-09 Aviv Orly

PieceWise Affine (PWA) approximations for nonlinear functions have been extensively used for tractable, computationally efficient control of nonlinear systems. However, reaching a desired approximation accuracy without prior information…

Systems and Control · Electrical Eng. & Systems 2025-11-04 Leila Gharavi , Bart De Schutter , Simone Baldi

We propose a family of variational approximations to Bayesian posterior distributions, called $\alpha$-VB, with provable statistical guarantees. The standard variational approximation is a special case of $\alpha$-VB with $\alpha=1$. When…

Statistics Theory · Mathematics 2018-02-09 Yun Yang , Debdeep Pati , Anirban Bhattacharya

In this article, we study algebraic decompositions and secondary constructions of almost perfect nonlinear (APN) functions. In many cases, we establish precise criteria which characterize when certain modifications of a given APN function…

Combinatorics · Mathematics 2025-01-08 Hiroaki Taniguchi , Alexandr Polujan , Alexander Pott , Razi Arshad

It is well-known that curvelets provide optimal approximations for so-called cartoon images which are defined as piecewise $C^2$-functions, separated by a $C^2$ singularity curve. In this paper, we consider the more general case of…

Functional Analysis · Mathematics 2014-04-04 Philipp Grohs , Sandra Keiper , Gitta Kutyniok , Martin Schäfer

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

This paper investigates the approximation properties of deep neural networks with piecewise-polynomial activation functions. We derive the required depth, width, and sparsity of a deep neural network to approximate any H\"{o}lder smooth…

Numerical Analysis · Mathematics 2022-12-06 Denis Belomestny , Alexey Naumov , Nikita Puchkin , Sergey Samsonov

We establish inverse and direct theorems on best approximations in quasi-normed Abelian groups through bilateral Bernstein-Jackson inequalities with exact constants. Using integral representations for quasi-norms of functions $f$ in…

Functional Analysis · Mathematics 2024-10-22 Oleh Lopushansky

Assume a L\'evy process $X$ on the time interval $[0,1]$ that is an $L_2$-martingale and let $Y$ be either its stochastic exponential or $X$ itself. We consider Riemann-approximations of certain stochastic integrals driven by $Y$ and relate…

Probability · Mathematics 2012-01-04 Christel Geiss , Stefan Geiss , Eija Laukkarinen

The regularity of refinable functions has been investigated deeply in the past 25 years using Fourier analysis, wavelet analysis, restricted and joint spectral radii techniques. However the shift-invariance of the underlying regular setting…

Numerical Analysis · Mathematics 2018-07-31 Maria Charina , Costanza Conti , Lucia Romani , Joachim Stöckler , Alberto Viscardi
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