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A geometry-based density functional theory is presented for mixtures of hard spheres, hard needles and hard platelets; both the needles and the platelets are taken to be of vanishing thickness. Geometrical weight functions that are…

Soft Condensed Matter · Physics 2009-11-11 Ansgar Esztermann , Hendrik Reich , Matthias Schmidt

Several problems in computer algebra can be efficiently solved by reducing them to calculations over finite fields. In this paper, we describe an algorithm for the reconstruction of multivariate polynomials and rational functions from their…

High Energy Physics - Phenomenology · Physics 2016-12-14 Tiziano Peraro

In this paper, we study functional approximations where we choose the so-called radial basis function method and more specifically, quasi-interpolation. From the various available approaches to the latter, we form new quasi-Lagrange…

Numerical Analysis · Mathematics 2023-09-07 Martin Buhmann , Janin Jäger , Joaquín Jódar , Miguel L. Rodríguez

We consider an important class of derivative contracts written on multiple assets (so-called spread options) which are traded on a wide range of financial markets. The present paper introduces a new approximation method of density functions…

Probability · Mathematics 2013-09-19 Alexander Kushpel

Approximation of scattered geometric data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This method is useful for…

Graphics · Computer Science 2018-04-19 Zuzana Majdisova , Vaclav Skala

Accurate interpolation and approximation techniques for functions with discontinuities are key tools in many applications as, for instance, medical imaging. In this paper, we study an RBF type method for scattered data interpolation that…

Numerical Analysis · Mathematics 2019-03-08 Stefano De Marchi , Wolfgang Erb , Francesco Marchetti , Emma Perracchione , Milvia Rossini

An inverse nonequispaced fast Fourier transform (iNFFT) is a fast algorithm to compute the Fourier coefficients of a trigonometric polynomial from nonequispaced sampling data. However, various applications such as magnetic resonance imaging…

Numerical Analysis · Mathematics 2025-06-09 Melanie Kircheis , Daniel Potts

Spectral density functions quantify how environmental modes couple to quantum systems and govern their open dynamics. Inferring such frequency-dependent functions from time-domain measurements is an ill-conditioned inverse problem. Here, we…

We consider the problem of interpolating a function given on scattered points using Hermite-Birkhoff formulas on the sphere and other manifolds. We express each proposed interpolant as a linear combination of basis functions, the…

Numerical Analysis · Mathematics 2016-11-23 Giampietro Allasia , Roberto Cavoretto , Alessandra De Rossi

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala

In this paper we introduce reproducing kernel Hilbert spaces of polyanalytic functions of infinite order. First we study in details the counterpart of the Fock space and related results in this framework. In this case the kernel function is…

Complex Variables · Mathematics 2021-12-30 Daniel Alpay , Fabrizio Colombo , Kamal Diki , Irene Sabadini

We study algorithms to estimate geometric properties of raw point cloud data through implicit surface representations. Given that any level-set function with a constant level set corresponding to the surface can be used for such…

Numerical Analysis · Mathematics 2026-04-02 Alex Shiu Lun Chu , Leevan Ling , Ka Chun Cheung

A number of applications in engineering, social sciences, physics, and biology involve inference over networks. In this context, graph signals are widely encountered as descriptors of vertex attributes or features in graph-structured data.…

Machine Learning · Statistics 2016-12-21 Daniel Romero , Meng Ma , Georgios B. Giannakis

We revisit the classical kernel method of approximation/interpolation theory in a very specific context motivated by the desire to obtain a robust procedure to approximate discrete data sets by (super)level sets of functions that are merely…

Machine Learning · Computer Science 2022-09-14 Patrick Guidotti

In this dissertation, it is first shown that, when the radial basis function is a $p$-norm and $1 < p < 2$, interpolation is always possible when the points are all different and there are at least two of them. We then show that…

Numerical Analysis · Mathematics 2010-06-15 Brad Baxter

We discuss and compare various approaches to the problem of bandwidth selection for kernel estimators of intensity functions of spatial point processes. We also propose a new method based on the Campbell formula applied to the reciprocal…

Methodology · Statistics 2016-12-01 O. Cronie , M. N. M. van Lieshout

The interpolation-regression approximation is a powerful tool in numerical analysis for reconstructing functions defined on square or triangular domains from their evaluations at a regular set of nodes. The importance of this technique lies…

Numerical Analysis · Mathematics 2025-08-12 Francesco Dell'Accio , Francisco Marcellán , Federico Nudo

Consider the problem when $X_1,X_2,..., X_n$ are distributed on a circle following an unknown distribution $F$ on $S^1$. In this article we have consider the absolute general set-up where the density can have local features such as…

Methodology · Statistics 2016-11-26 Kinjal Basu , Debapriya Sengupta

The Hermite-Birkhoff interpolation problem of a function given on arbitrarily distributed points on the sphere and other manifolds is considered. Each proposed interpolant is expressed as a linear combination of basis functions, the…

Numerical Analysis · Mathematics 2017-05-03 Giampietro Allasia , Roberto Cavoretto , Alessandra De Rossi

We provide sufficient conditions on a family of functions $(\phi_\alpha)_{\alpha\in A}:\mathbb{R}^d\to\mathbb{R}$ for sampling of multivariate bandlimited functions at certain nonuniform sequences of points in $\mathbb{R}^d$. We consider…

Functional Analysis · Mathematics 2018-02-14 Keaton Hamm