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Numerical integration is encountered in all fields of numerical analysis and the engineering sciences. By now, various efficient and accurate quadrature rules are known; for instance, Gauss-type quadrature rules. In many applications,…

Numerical Analysis · Mathematics 2021-02-24 Jan Glaubitz

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

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

Positive interpolatory cubature formulas (CFs) are constructed for quite general integration domains and weight functions. These CFs are exact for general vector spaces of continuous real-valued functions that contain constants. At the same…

Numerical Analysis · Mathematics 2020-09-28 Jan Glaubitz

Fractional difference equations provide a flexible mathematical framework for modeling complex systems with memory, hereditary, and non-local effects. In this work, we study the stability of higher-order two-term fractional linear…

Dynamical Systems · Mathematics 2026-03-25 Janardhan Chevala , Sachin Bhalekar

The cubature on Wiener space method, a high-order weak approximation scheme, is established for SPDEs in the case of unbounded characteristics and unbounded payoffs. We first introduce a recently described flexible functional analytic…

Probability · Mathematics 2012-01-20 Philipp Doersek , Josef Teichmann , Dejan Veluscek

Many applications require multi-dimensional numerical integration, often in the form of a cubature formula. These cubature formulas are desired to be positive and exact for certain finite-dimensional function spaces (and weight functions).…

Numerical Analysis · Mathematics 2022-05-27 Jan Glaubitz

The goal of the paper is to establish cubature formulas on combinatorial graphs. Two types of cubature formulas are developed. Cubature formulas of the first type are exact on spaces of variational splines on graphs. Since badlimited…

Functional Analysis · Mathematics 2019-04-18 Isaac Z. Pesenson , Meyer Z. Pesenson , Hartmut F"uhr

We construct an interpolatory high-order cubature rule to compute integrals of smooth functions over self-affine sets with respect to an invariant measure. The main difficulty is the computation of the cubature weights, which we…

Numerical Analysis · Mathematics 2025-12-16 Patrick Joly , Maryna Kachanovska , Zoïs Moitier

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

A stability analysis is performed on high-order schemes formulated using the Flux Reconstruction (FR) approach. The one-dimensional advection model equation is used for the assessment of the stability region of these schemes when coupled…

Fluid Dynamics · Physics 2023-08-21 Frederico Bolsoni Oliveira , João Luiz F. Azevedo

Quadrature formulas for spheres, the rotation group, and other compact, homogeneous manifolds are important in a number of applications and have been the subject of recent research. The main purpose of this paper is to study coordinate…

Numerical Analysis · Mathematics 2012-11-26 E. Fuselier , T. Hangelbroek , F. J. Narcowich , J. D. Ward , G. B. Wright

When the dynamical data of a system only convey dynamic information over a limited operating range, the identification of models with good performance over a wider operating range is very unlikely. Nevertheless, models with such…

Systems and Control · Electrical Eng. & Systems 2020-09-07 Leandro Freitas , Bruno H. G. Barbosa , Luis A. Aguirre

The work reported in this article presents a high-order, stable, and efficient Gegenbauer pseudospectral method to solve numerically a wide variety of mathematical models. The proposed numerical scheme exploits the stability and the…

Numerical Analysis · Mathematics 2023-03-06 Kareem T. Elgindy

Heavy-tailed distributions are widely used in robust mixture modelling due to possessing thick tails. As a computationally tractable subclass of the stable distributions, sub-Gaussian $\alpha$-stable distribution received much interest in…

Machine Learning · Statistics 2017-01-25 Mahdi Teimouri , Saeid Rezakhah , Adel Mohammdpour

Collaborative filtering (CF) is a popular technique in today's recommender systems, and matrix approximation-based CF methods have achieved great success in both rating prediction and top-N recommendation tasks. However, real-world…

Machine Learning · Computer Science 2018-11-07 Dongsheng Li , Chao Chen , Qin Lv , Junchi Yan , Li Shang , Stephen M. Chu

We propose and analyse randomized cubature formulae for the numerical integration of functions with respect to a given probability measure $\mu$ defined on a domain $\Gamma \subseteq \mathbb{R}^d$, in any dimension $d$. Each cubature…

Numerical Analysis · Mathematics 2020-12-04 Giovanni Migliorati , Fabio Nobile

We study the numerical algorithm and error analysis for the Cahn-Hilliard equation with dynamic boundary conditions. A second-order in time, linear and energy stable scheme is proposed, which is an extension of the first-order stabilized…

Numerical Analysis · Mathematics 2022-06-16 Xiangjun Meng , Xuelian Bao , Zhengru Zhang

Gau{\ss} cubature (multidimensional numerical integration) rules are the natural generalisation of the 1D Gau{\ss} rules. They are optimal in the sense that they exactly integrate polynomials of as high a degree as possible for a particular…

Numerical Analysis · Mathematics 2025-10-20 David De Wit

To predict allowable time-step size for the fully discretized nonlinear differential equations, a stability theory is developed using exact determination of an infinite perturbation series. Mathematical induction is used to determine the…

Numerical Analysis · Mathematics 2013-11-05 Arash Ghasemi , Kidambi Sreenivas , Lafayette K. Taylor

In this paper, we present a new data-driven method for learning stable models of nonlinear systems. Our model lifts the original state space to a higher-dimensional linear manifold using Koopman embeddings. Interestingly, we prove that…

Machine Learning · Computer Science 2021-10-14 Fletcher Fan , Bowen Yi , David Rye , Guodong Shi , Ian R. Manchester
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