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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…

Least squares estimation, a regression technique based on minimisation of residuals, has been invaluable in bringing the best fit solutions to parameters in science and engineering. However, in dynamic environments such as in Geomatics…

Computational Engineering, Finance, and Science · Computer Science 2018-04-17 C. P. E. Agbachi

A first-order system least squares formulation for the sea-ice dynamics is presented. In addition to the displacement field, the stress tensor is used as a variable. As finite element spaces, standard conforming piecewise polynomials for…

Numerical Analysis · Mathematics 2018-09-06 Fleurianne Bertrand

We propose a mixed finite element method for Stokes flow with one degree of freedom per element and facet of simplicial grids. The method is derived by considering the vorticity-velocity-pressure formulation and eliminating the vorticity…

Numerical Analysis · Mathematics 2022-08-30 Wietse M. Boon , Alessio Fumagalli

We propose a First-Order System Least Squares (FOSLS) method based on deep-learning for numerically solving second-order elliptic PDEs. The method we propose is capable of dealing with either variational and non-variational problems, and…

Numerical Analysis · Mathematics 2022-12-15 Francisco M. Bersetche , Juan Pablo Borthagaray

We propose a posteriori error estimators for classical low-order inf-sup stable and stabilized finite element approximations of the Stokes problem with singular sources in two and three dimensional Lipschitz, but not necessarily convex,…

Numerical Analysis · Mathematics 2019-01-30 Alejandro Allendes , Enrique Otarola , Abner J. Salgado

This paper is concerned with stochastic incompressible Navier-Stokes equations with multiplicative noise in two dimensions with respect to periodic boundary conditions. Based on the Helmholtz decomposition of the multiplicative noise,…

Numerical Analysis · Mathematics 2022-11-28 Hailong Qiu

We address the phase retrieval problem with errors in the sensing vectors. A number of recent methods for phase retrieval are based on least squares (LS) formulations which assume errors in the quadratic measurements. We extend this…

Signal Processing · Electrical Eng. & Systems 2022-02-02 Sidharth Gupta , Ivan Dokmanić

This paper is concerned with function reconstruction from samples. The sampling points used in several approaches are (1) structured points connected with fast algorithms or (2) unstructured points coming from, e.g., an initial random draw…

Numerical Analysis · Mathematics 2023-06-07 Felix Bartel , Lutz Kämmerer , Daniel Potts , Tino Ullrich

In this paper, two flux-only least-squares finite element methods (LSFEM) for the linear hyperbolic transport problem are developed. The transport equation often has discontinuous solutions and discontinuous inflow boundary conditions, but…

Numerical Analysis · Mathematics 2019-07-17 Qunjie Liu , Shun Zhang

In the usual trace reconstruction problem, the goal is to exactly reconstruct an unknown string of length $n$ after it passes through a deletion channel many times independently, producing a set of traces (i.e., random subsequences of the…

Data Structures and Algorithms · Computer Science 2020-12-17 Sami Davies , Miklos Z. Racz , Cyrus Rashtchian , Benjamin G. Schiffer

We consider a polynomial reconstruction of smooth functions from their noisy values at discrete nodes on the unit sphere by a variant of the regularized least-squares method of An et al., SIAM J. Numer. Anal. 50 (2012), 1513--1534. As nodes…

Numerical Analysis · Mathematics 2015-01-12 Sergei. V. Pereverzyev , Ian. H. Sloan , Pavlo Tkachenko

We prove the contraction property for two successive loops of the adaptive algorithm for the Stokes problem reducing the error of the velocity. The problem is discretized by a divergence-conforming discontinuous Galerkin method which…

Numerical Analysis · Mathematics 2018-07-24 Natasha Sharma , Guido Kanschat

Based on the auxiliary subspace techniques, a hierarchical basis a posteriori error estimator is proposed for the Stokes problem in two and three dimensions. For the error estimator, we need to solve only two global diagonal linear systems…

Numerical Analysis · Mathematics 2023-03-22 Jiachuan Zhang , Ran Zhang , Xiaoshen Wang

We approximate the solution of the stationary Stokes equations with various conforming and nonconforming inf-sup stable pairs of finite element spaces on simplicial meshes. Based on each pair, we design a discretization that is…

Numerical Analysis · Mathematics 2019-02-12 Christian Kreuzer , Pietro Zanotti

We construct several stable finite element pairs for the Stokes problem on barycentric refinements in arbitrary dimensions. A key feature of the spaces is that the divergence maps the discrete velocity space onto the the discrete pressure…

Numerical Analysis · Mathematics 2017-10-24 Johnny Guzman , Michael Neilan

Least squares (LS) fitting is one of the most fundamental techniques in science and engineering. It is used to estimate parameters from multiple noisy observations. In many problems the parameters are known a-priori to be bounded integer…

Information Theory · Computer Science 2009-01-05 Amir Leshem , Jacob Goldberger

In this paper, the stabilized finite element method based on local projection is applied to discretize the Stokes eigenvalue problems and the corresponding convergence analysis is given. Furthermore, we also use a method to improve the…

Numerical Analysis · Mathematics 2011-12-30 Hehu Xie

This work proposes a new stabilized $P_1\times P_0$ finite element method for solving the incompressible Navier--Stokes equations. The numerical scheme is based on a reduced Bernardi--Raugel element with statically condensed face bubbles…

Numerical Analysis · Mathematics 2023-04-06 Yuwen Li , Ludmil Zikatanov

We introduce a method to reconstruct an element of a Hilbert space in terms of an arbitrary finite collection of linearly independent reconstruction vectors, given a finite number of its samples with respect to any Riesz basis. As we…

Numerical Analysis · Mathematics 2010-12-01 Ben Adcock , Anders C. Hansen