English
Related papers

Related papers: Least-squares for linear elasticity eigenvalue pro…

200 papers

A nonlinear small-strain elastic theory is constructed from a systematic expansion in Biot strains, truncated at quadratic order. The primary motivation is the desire for a clean separation between stretching and bending energies for…

Soft Condensed Matter · Physics 2021-07-12 E. Vitral , J. A. Hanna

We study theoretical and computational aspects of the least squares fit (LSF) of circles and circular arcs. First we discuss the existence and uniqueness of LSF and various parametrization schemes. Then we evaluate several popular circle…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 N. Chernov , C. Lesort

The aim of this article is to overview the problem of mean square optimal estimation of linear functionals which depend on unknown values of periodically correlated stochastic process. Estimates are based on observations of this process and…

Statistics Theory · Mathematics 2025-11-24 Iryna Dubovets'ka , Mykhailo Moklyachuk

In this paper, a few dual least-squares finite element methods and their application to scalar linear hyperbolic problems are studied. The purpose is to obtain $L^2$-norm approximations on finite element spaces of the exact solutions to…

Numerical Analysis · Mathematics 2020-10-06 Delyan Z. Kalchev , Thomas A. Manteuffel , Steffen Münzenmaier

The discrete Laplace operator on a triangulated polyhedral surface is related to geometric properties of the surface. This paper studies extremum problems for eigenvalues of the discrete Laplace operators. Among all triangles, an…

Metric Geometry · Mathematics 2011-06-30 Ren Guo

The modeling of the elastic properties of disordered or nanoscale solids requires the foundations of the theory of elasticity to be revisited, as one explores scales at which this theory may no longer hold. The only cases for which…

Materials Science · Physics 2007-05-23 I. Goldhirsch , C. Goldenberg

In this paper, we construct new finite element methods for the approximation of the equations of linear elasticity in three space dimensions that produce direct approximations to both stresses and displacements. The methods are based on a…

Numerical Analysis · Mathematics 2014-01-29 Douglas N. Arnold , Richard S. Falk , Ragnar Winther

This paper is concerned with the design and analysis of least squares solvers for ill-posed PDEs that are conditionally stable. The norms and the regularization term used in the least squares functional are determined by the ingredients of…

Numerical Analysis · Mathematics 2023-06-02 Wolfgang Dahmen , Harald Monsuur , Rob Stevenson

We develop a finite element discretization for the weakly symmetric equations of linear elasticity on tetrahedral meshes. The finite element combines, for $r \geq 0$, discontinuous polynomials of $r$ for the displacement,…

Numerical Analysis · Mathematics 2018-02-09 Tobin Isaac

Rational approximation appears in many contexts throughout science and engineering, playing a central role in linear systems theory, special function approximation, and many others. There are many existing methods for solving the rational…

Numerical Analysis · Mathematics 2018-12-03 Jeffrey M. Hokanson , Caleb C. Magruder

We present a hierarchy of tractable relaxations to obtain lower bounds on the minimum value of a polynomial over a constraint set defined by polynomial equations. In contrast to previous convex relaxation techniques for this problem, our…

Optimization and Control · Mathematics 2025-07-23 Elvira Moreno , Venkat Chandrasekaran

Given $n$ samples of a function $f\colon D\to\mathbb C$ in random points drawn with respect to a measure $\varrho_S$ we develop theoretical analysis of the $L_2(D, \varrho_T)$-approximation error. For a parituclar choice of $\varrho_S$…

Numerical Analysis · Mathematics 2024-08-29 Felix Bartel

We study the asymptotic behaviour of the eigenvalues of the Laplace-Beltrami operator on a compact hypersurface in \mathds{R}^{n+1} as it is flattened into a singular double-sided flat hypersurface. We show that the limit spectral problem…

Analysis of PDEs · Mathematics 2016-01-20 Denis Borisov , Pedro Freitas

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result. The output allows…

Machine Learning · Computer Science 2024-07-17 Roberto Esposito , Mattia Cerrato , Marco Locatelli

Given a sequence of Marcinkiewicz-Zygmund inequalities in $L_2$ on a usual compact space $\mathcal M$, Gr\"ochenig introduced the weighted least squares polynomials and the least squares quadrature from pointwise samples of a function, and…

Numerical Analysis · Mathematics 2021-01-12 Wanting Lu , Heping Wang

We consider singular perturbed eigenvalue problem for Laplace operator in a cylinder with frequent and nonperiodic alternation of boundary conditions imposed on narrow strips lying in the lateral surface. The width of strips depends on a…

Mathematical Physics · Physics 2015-06-26 Denis I. Borisov

We determine the general form of the asymptotics for Dirichlet eigenvalues of the one-dimensional linear damped wave operator. As a consequence, we obtain that given a spectrum corresponding to a constant damping term this determines the…

Spectral Theory · Mathematics 2009-05-21 Denis Borisov , Pedro Freitas

This article investigates the least squares estimators (LSE) for the unknown parameters in stochastic differential equations (SDEs) that are affected by L\'evy noise, particularly when the sample paths are sparse. Specifically, given $n$…

Methodology · Statistics 2026-01-01 Brijesh Kumar Jha , Subhra Sankar Dhar , Akash Ashirbad Panda

We derive the equations of nonlinear electroelastostatics using three different variational formulations involving the deformation function and an independent field variable representing the electric character - considering either one of…

Classical Physics · Physics 2023-12-21 Prashant Saxena , Basant Lal Sharma

Linear Least Squares is a very well known technique for parameter estimation, which is used even when sub-optimal, because of its very low computational requirements and the fact that exact knowledge of the noise statistics is not required.…

Statistics Theory · Mathematics 2018-10-16 Michael Krikheli , Amir Leshem