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This article shows that on a closed interval $[a,b]$ a continuous function may be approximated to an arbitrary degree of accuracy using scattered translates of the general multiquadric $(x^2+c^2)^{k-1/2}$.

Functional Analysis · Mathematics 2013-06-28 Jeff Ledford

The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated shifts of a smooth and rapidly decaying function on a uniform grid to scattered data quasi-interpolation. It is shown that high order…

Numerical Analysis · Mathematics 2007-05-23 F. Lanzara , V. Maz'ya , G. Schmidt

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

We prove the existence of entire functions that achieve universal approximations on certain countable sequences of translation operators .

Functional Analysis · Mathematics 2022-02-22 Nikos Tsirivas

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

Kernel based regularized interpolation is a well known technique to approximate a continuous multivariate function using a set of scattered data points and the corresponding function evaluations, or data values. This method has some…

Numerical Analysis · Mathematics 2018-07-26 Gabriele Santin , Dominik Wittwar , Bernard Haasdonk

The purpose of this note is to compare various approximation methods as applied to the inverse of the Bessel function of the first kind, in a given domain of the complex plane.

Numerical Analysis · Mathematics 2018-01-11 D. S. Karachalios , I. V. Gosea , Q. Zhang , A. C. Antoulas

The paper is concerned with the equilibrium distributions of continuous-time density dependent Markov processes on the integers. These distributions are known typically to be approximately normal, and the approximation error, as measured in…

Probability · Mathematics 2009-02-06 Sanda N. Socoll , A. D. Barbour

It is shown that the method of exchangeable pairs introduced by Stein [Approximate Computation of Expectations (1986) IMS, Hayward, CA] for normal approximation can effectively be used for translated Poisson approximation. Introducing an…

Probability · Mathematics 2010-04-06 Adrian Röllin

In this paper we provide a rigorous mathematical foundation for continuous approximations of a class of systems with piece-wise continuous functions. By using techniques from the theory of differential inclusions, the underlying piece-wise…

Chaotic Dynamics · Physics 2014-08-20 Marius-F. Danca

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances. A convergence theory for iterated random functions is…

Machine Learning · Statistics 2013-11-05 Arash A. Amini , XuanLong Nguyen

This paper is concerned with the analysis of the kernel-based algorithm for gain function approximation in the feedback particle filter. The exact gain function is the solution of a Poisson equation involving a probability-weighted…

Numerical Analysis · Mathematics 2016-12-19 Amirhossein Taghvaei , Prashant G. Mehta , Sean P. Meyn

This paper addresses the problem of approximating a function of bounded variation from its scattered data. Radial basis function(RBF) interpolation methods are known to approximate only functions in their native spaces, and to date, there…

Numerical Analysis · Mathematics 2025-12-23 Rajesh Dachiraju

In this article we propose building general-purpose function approximators on top of Haar Scattering Networks. We advocate that this architecture enables a better comprehension of feature extraction, in addition to its implementation…

Machine Learning · Statistics 2018-04-11 Fernando Fernandes Neto

We address the problem of approximating an unknown function from its discrete samples given at arbitrarily scattered sites. This problem is essential in numerical sciences, where modern applications also highlight the need for a solution to…

Numerical Analysis · Mathematics 2023-05-16 Nir Sharon , Rafael Sherbu Cohen , Holger Wendland

The idea behind Poisson approximation to the binomial distribution was used in [J. de la Cal, F. Luquin, J. Approx. Theory, 68(3), 1992, 322-329] and subsequent papers in order to establish the convergence of suitable sequences of positive…

Probability · Mathematics 2022-08-18 Ana-Maria Acu , Margareta Heilmann , Ioan Rasa , Andra Seserman

It is well known that a binomial $(n,p)$ can be approximated by a Poisson distribution with parameter $np$. The typical approach in undergraduate probability texts is to show a convergence result for the distribution of the binomial as $n$…

Probability · Mathematics 2026-05-05 Rinaldo B. Schinazi

In this paper we analyze a greedy procedure to approximate a linear functional defined in a Reproducing Kernel Hilbert Space by nodal values. This procedure computes a quadrature rule which can be applied to general functionals, including…

Numerical Analysis · Mathematics 2021-05-19 Gabriele Santin , Toni Karvonen , Bernard Haasdonk

A new approach to Poisson approximation is proposed. The basic idea is very simple and based on properties of the Charlier polynomials and the Parseval identity. Such an approach quickly leads to new effective bounds for several Poisson…

Probability · Mathematics 2010-07-29 Vytas Zacharovas , Hsien-Kuei Hwang

Fixpoints are ubiquitous in computer science and when dealing with quantitative semantics and verification one often considers least fixpoints of (higher-dimensional) functions over the non-negative reals. We show how to approximate the…

Logic in Computer Science · Computer Science 2025-06-16 Paolo Baldan , Sebastian Gurke , Barbara König , Tommaso Padoan , Florian Wittbold
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