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The Lane-Emden type equations are employed in the modelling of several phenomena in the areas of mathematical physics and astrophysics . In this paper a new numerical method is applied to investigate some well-known classes of Lane-Emden…

Numerical Analysis · Mathematics 2016-05-27 Kourosh Parand , Soleiman Hashemi

When solving partial differential equations on scattered nodes using the Radial Basis Function generated Finite Difference (RBF-FD) method, one of the parameters that must be chosen is the stencil size. Focusing on Polyharmonic Spline RBFs…

Numerical Analysis · Mathematics 2026-02-26 Andrej Kolar-Požun , Mitja Jančič , Miha Rot , Gregor Kosec

A generalization of the Gr\"{u}nwald difference approximation for fractional derivatives in terms of a real sequence and its generating function is presented. Properties of the generating function are derived for consistency and order of…

Numerical Analysis · Mathematics 2018-03-06 H. M. Nasir , K. Nafa

We propose two localized Radial Basis Function (RBF) methods, the Radial Basis Function Partition of Unity method (RBF-PUM) and the Radial Basis Function generated Finite Differences method (RBF-FD), for solving financial derivative pricing…

Computational Finance · Quantitative Finance 2018-08-20 Slobodan Milovanović , Victor Shcherbakov

Scientific studies often require the precise calculation of derivatives. In many cases an analytical calculation is not feasible and one resorts to evaluating derivatives numerically. These are error-prone, especially for higher-order…

High Energy Physics - Phenomenology · Physics 2010-05-28 Mathias Wagner , Andrea Walther , Bernd-Jochen Schaefer

We describe a method for calculating the roots of special functions satisfying second order linear ordinary differential equations. It exploits the recent observation that the solutions of a large class of such equations can be represented…

Numerical Analysis · Mathematics 2016-08-05 James Bremer

In this paper we present a new fast and accurate method for Radial Basis Function (RBF) approximation, including interpolation as a special case, which enables us to effectively find the optimal value of the RBF shape parameter. In…

Numerical Analysis · Mathematics 2023-11-09 Roberto Cavoretto , Alessandra De Rossi , Sandro Lancellotti

Because of the nonlocal properties of fractional operators, higher order schemes play more important role in discretizing fractional derivatives than classical ones. The striking feature is that higher order schemes of fractional…

Numerical Analysis · Mathematics 2014-06-17 Minghua Chen , Weihua Deng

We show how rational function approximations to the logarithm, such as $\log z \approx (z^2 - 1)/(z^2 + 6z + 1)$, can be turned into fast algorithms for approximating the determinant of a very large matrix. We empirically demonstrate that…

Data Structures and Algorithms · Computer Science 2024-05-07 Thomas Colthurst , Srinivas Vasudevan , James Lottes , Brian Patton

We present an approach to reduced-order modelling that builds off recent graph-theoretic work for representation, exploration, and analysis of computed states of physical systems (Banerjee et al., Comp. Meth. App. Mech. Eng., 351, 501-530,…

Numerical Analysis · Mathematics 2022-12-21 Matthew Duschenes , Siddhartha Srivastava , Krishna Garikipati

Multisite local orbitals, which are formed from linear combinations of pseudo-atomic orbitals from a target atom and its neighbor atoms, have been introduced in the large-scale density functional theory calculation code CONQUEST. Multisite…

Materials Science · Physics 2014-11-11 Ayako Nataka , David R. Bowler , Tsuyoshi Miyazaki

High-order derivatives of analytic functions are expressible as Cauchy integrals over circular contours, which can very effectively be approximated, e.g., by trapezoidal sums. Whereas analytically each radius r up to the radius of…

Numerical Analysis · Mathematics 2011-04-04 Folkmar Bornemann

In this study, we examine numerical approximations for 2nd-order linear-nonlinear differential equations with diverse boundary conditions, followed by the residual corrections of the first approximations. We first obtain numerical results…

Numerical Analysis · Mathematics 2023-06-19 Shovan Sourav Datta Pranta , Md. Shafiqul Islam

Radial Basis Function (RBF), or Gaussian, kernels are among the most widely used parametric kernels in machine learning, particularly in methods such as Support Vector Machines (SVM) and kernel-based subspace approaches. The kernel…

General Mathematics · Mathematics 2026-04-03 Lakhdar Remaki

Generalized trigonometric functions (GTFs) are simple generalization of the classical trigonometric functions. GTFs are deeply related to the $p$-Laplacian, which is known as a typical nonlinear differential operator, and there are a lot of…

Classical Analysis and ODEs · Mathematics 2019-03-20 Hiroyuki Kobayashi , Shingo Takeuchi

A general and easy-to-code numerical method based on radial basis functions (RBFs) collocation is proposed for the solution of delay differential equations (DDEs). It relies on the interpolation properties of infinitely smooth RBFs, which…

Numerical Analysis · Mathematics 2017-01-03 Francisco Bernal , Gail Gutiérrez

It is well known that using high-order numerical algorithms to solve fractional differential equations leads to almost the same computational cost with low-order ones but the accuracy (or convergence order) is greatly improved, due to the…

Numerical Analysis · Mathematics 2017-05-25 Hengfei Ding , Changpin Li

In this paper, a new localized radial basis function (RBF) method based on partition of unity (PU) is proposed for solving boundary and initial-boundary value problems. The new method is benefited from a direct discretization approach and…

Numerical Analysis · Mathematics 2020-10-28 Davoud Mirzaei

Quadrature formulas (QFs) based on radial basis functions (RBFs) have become an essential tool for multivariate numerical integration of scattered data. Although numerous works have been published on RBF-QFs, their stability theory can…

Numerical Analysis · Mathematics 2023-01-31 Jan Glaubitz , Jonah A. Reeger

In this paper, we study the benefits of using polyharmonic splines and node layouts with smoothly varying density for developing robust and efficient radial basis function generated finite difference (RBF-FD) methods for pricing of…

Computational Finance · Quantitative Finance 2018-08-20 Slobodan Milovanović