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In this paper, we investigate the problem of designing compact support interpolation kernels for a given class of signals. By using calculus of variations, we simplify the optimization problem from an infinite nonlinear problem to a finite…

Multimedia · Computer Science 2011-05-03 Ramtin Madani , Ali Ayremlou , Arash Amini , Farrokh Marvasti

In this paper, we give a causal solution to the problem of spline interpolation using H-infinity optimal approximation. Generally speaking, spline interpolation requires filtering the whole sampled data, the past and the future, to…

Information Theory · Computer Science 2013-08-14 Masaaki Nagahara , Yutaka Yamamoto

The paper deals with two fundamental types of trigonometric polynomials and splines on uniform grids, which allow us to construct interpolation approximations that depend linearly on the values of the interpolated function. Fundamental on…

Numerical Analysis · Mathematics 2019-12-05 V. P. Denysiuk

We present a generalized formulation for reweighted least squares approximations. The goal of this article is twofold: firstly, to prove that the solution of such problem can be expressed as a convex combination of certain interpolants when…

Interpolation by various types of splines is the standard procedure in many applications. In this paper we shall discuss harmonic spline "interpolation" (on the lines of a grid) as an alternative to polynomial spline interpolation (at…

Numerical Analysis · Mathematics 2011-01-17 Yuliya Babenko , Tatyana Leskevich

This paper provides approximation orders for a class of nonlinear interpolation procedures for univariate data sampled over $\sigma$ quasi-uniform grids. The considered interpolation is built using both essentially nonoscillatory (ENO) and…

Numerical Analysis · Mathematics 2026-04-10 J. A. Padilla , J. C. Trillo

In areas such as kernel smoothing and non-parametric regression there is emphasis on smooth interpolation and smooth statistical models. Splines are known to have optimal smoothness properties in one and higher dimensions. It is shown, with…

Computation · Statistics 2008-09-29 Ron A. Bates , Hugo Maruri-Aguilar , Henry P. Wynn

We consider an overdetermined problem for Laplace equation on a disk with partial boundary data where additional pointwise data inside the disk have to be taken into account. After reformulation, this ill-posed problem reduces to a bounded…

Analysis of PDEs · Mathematics 2015-08-17 Laurent Baratchart , Juliette Leblond , Dmitry Ponomarev

In this paper, we formally investigate two mathematical aspects of Hermite splines which translate to features that are relevant to their practical applications. We first demonstrate that Hermite splines are maximally localized in the sense…

Numerical Analysis · Mathematics 2019-02-11 Julien Fageot , Shayan Aziznejad , Michael Unser , Virginie Uhlmann

In the present paper, using S.L. Sobolev's method, interpolation spline that minimizes the expression $\int_0^1(\varphi^{(m)}(x)+\omega^2\varphi^{(m-2)}(x))^2dx$ in the $K_2(P_m)$ space are constructed. Explicit formulas for the…

Numerical Analysis · Mathematics 2014-10-21 Abdullo R. Hayotov

The purpose of this article is to introduce a new class of kernels on SO(3) for approximation and interpolation, and to estimate the approximation power of the associated spaces. The kernels we consider arise as linear combinations of…

Classical Analysis and ODEs · Mathematics 2011-06-14 Thomas Hangelbroek , Dominik Schmid

In this paper, we study a class of approximation problems, appearing in data approximation and signal processing. The approximations are constructed as combinations of polynomial splines (piecewise polynomials), whose parameters are subject…

Optimization and Control · Mathematics 2015-03-05 Zahra Roshan Zamir , Nadezda Sukhorukova

In this paper we consider the approximation of functions by radial basis function interpolants. There is a plethora of results about the asymptotic behaviour of the error between appropriately smooth functions and their interpolants, as the…

Numerical Analysis · Mathematics 2007-12-02 R. A. Brownlee , W. A. Light

In this paper, we propose a meshfree approximation method for the implicit filter developed in [2], which is a novel numerical algorithm for nonlinear filtering problems. The implicit filter approximates conditional distributions in the…

Numerical Analysis · Mathematics 2015-08-05 Feng Bao , Yanzhao Cao , Clayton Webster , Guannan Zhang

The analysis of complex nonlinear systems is often carried out using simpler piecewise linear representations of them. A principled and practical technique is proposed to linearize and evaluate arbitrary continuous nonlinear functions using…

Optimization and Control · Mathematics 2017-11-10 Guillermo Gallego , Daniel Berjón , Narciso García

We develop a local polynomial spline interpolation scheme for arbitrary spline order on bounded intervals. Our method's local formulation, effective boundary considerations and optimal interpolation error rate make it particularly useful…

Numerical Analysis · Mathematics 2015-12-01 Maria D. van der Walt

The supply function equilibrium (SFE) is a model for competition in markets where each firm offers a schedule of prices and quantities to face demand uncertainty, and has been successfully applied to wholesale electricity markets. However,…

Optimization and Control · Mathematics 2015-02-05 Sheng Yu , Enrique Campos-Nanez

We present an $\ell^2_2+\ell_1$-regularized discrete least squares approximation over general regions under assumptions of hyperinterpolation, named hybrid hyperinterpolation. Hybrid hyperinterpolation, using a soft thresholding operator…

Numerical Analysis · Mathematics 2024-07-08 Congpei An , Jiashu Ran , Alvise Sommariva

The paper is devoted to the construction of an optimal interpolation formula in $K_2(P_2)$ Hilbert space. Here the interpolation formula consists of a linear combination $\sum_{\beta=0}^NC_{\beta}(z)\varphi(x_\beta)$ of given values of a…

Numerical Analysis · Mathematics 2020-04-07 S. S. Babaev

We introduce and analyze a framework for function interpolation using compressed sensing. This framework - which is based on weighted $\ell^1$ minimization - does not require a priori bounds on the expansion tail in either its…

Numerical Analysis · Mathematics 2017-01-24 Ben Adcock
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