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Related papers: Nonlinear nonnested 2-D spline approximation

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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

Contours may be viewed as the 2D outline of the image of an object. This type of data arises in medical imaging as well as in computer vision and can be modeled as data on a manifold and can be studied using statistical shape analysis.…

Applications · Statistics 2017-05-17 Chalani Prematilake , Leif Ellingson

We prove Inequalities similar to those of Bernstein for non-periodic splines in $L_2$ space.

Functional Analysis · Mathematics 2017-08-29 Vladislav Babenko , Susanna Spektor

We introduce here Cartesian splines or, for short, C-splines. C- splines are piecewise polynomials which are defined on adjacent Cartesian coordinate systems and are Cr continuous throughout. The Cr continuity is enforced by constraining…

Numerical Analysis · Mathematics 2014-09-23 H. R. N. van Erp , R. O. Linger , P. H. A. J. M. van Gelder

Two approximations of the integral of a class of sinusoidal composite functions, for which an explicit form does not exist, are derived. Numerical experiments show that the proposed approximations yield an error that does not depend on the…

Numerical Analysis · Mathematics 2024-01-17 Alberto Costa

In this paper, we present two choices of structured spectral gradient methods for solving nonlinear least-squares problems. In the proposed methods, the scalar multiple of identity approximation of the Hessian inverse is obtained by…

Optimization and Control · Mathematics 2018-07-31 Hassan Mohammad , Mohammed Yusuf Waziri

Nonlinear losses accompanying Kerr self-focusing substantially impacts the dynamic balance of diffraction and nonlinearity, permitting the existence of localized and stationary solutions of the 2D+1 nonlinear Schrodinger equation which are…

We show that for any uniformly parabolic fully nonlinear second-order equation with bounded measurable "coefficients" and bounded "free" term in the whole space or in any cylindrical smooth domain with smooth boundary data one can find an…

Analysis of PDEs · Mathematics 2013-06-11 N. V. Krylov

Generalizing tensor-product splines to smooth functions whose control nets outline topological polyhedra, bi-cubic polyhedral splines form a piecewise polynomial, first-order differentiable space that associates one function with each…

Numerical Analysis · Mathematics 2023-04-26 Bhaskar Mishra , Jorg Peters

Recent advances in the field of network embedding have shown that low-dimensional network representation is playing a critical role in network analysis. Most existing network embedding methods encode the local proximity of a node, such as…

Social and Information Networks · Computer Science 2019-06-11 Junliang Guo , Linli Xu , Jingchang Liu

A bivariate spline method is developed to numerically solve second order elliptic partial differential equations (PDE) in non-divergence form. The existence, uniqueness, stability as well as approximation properties of the discretized…

Numerical Analysis · Mathematics 2017-01-05 Ming-Jun Lai , Chunmei Wang

Multivariate piecewise polynomial functions (or splines) on polyhedral complexes have been extensively studied over the past decades and find applications in diverse areas of applied mathematics including numerical analysis, approximation…

Commutative Algebra · Mathematics 2021-07-15 Deepesh Toshniwal , Nelly Villamizar

Sparse learning is a very important tool for mining useful information and patterns from high dimensional data. Non-convex non-smooth regularized learning problems play essential roles in sparse learning, and have drawn extensive attentions…

Machine Learning · Computer Science 2020-10-22 Guannan Liang , Qianqian Tong , Jiahao Ding , Miao Pan , Jinbo Bi

Using neural networks to solve variational problems, and other scientific machine learning tasks, has been limited by a lack of consistency and an inability to exactly integrate expressions involving neural network architectures. We address…

Machine Learning · Computer Science 2021-10-28 Jonas A. Actor , Andy Huang , Nathaniel Trask

This article studies sufficient conditions on families of approximating kernels which provide $N$--term approximation errors from an associated nonlinear approximation space which match the best known orders of $N$--term wavelet expansion.…

Functional Analysis · Mathematics 2019-03-15 Keaton Hamm , Jeff Ledford

We determine simplicity criteria in characteristics 0 and $p$ for a ubiquitous class of iterated skew polynomial rings in two indeterminates over a base ring. One obstruction to simplicity is the possible existence of a canonical normal…

Rings and Algebras · Mathematics 2013-01-24 David A. Jordan , Imogen E. Wells

In this paper we study "discrete polynomial blending," a term used to define a certain discretized version of curve blending whereby one approximates from the "sum of tensor product polynomial spaces" over certain grids. Our strategy is to…

Numerical Analysis · Mathematics 2017-04-28 Scott Kersey

In this paper, we consider the problem of piecewise affine abstraction of nonlinear systems, i.e., the overapproximation of its nonlinear dynamics by a pair of piecewise affine functions that "includes" the dynamical characteristics of the…

Optimization and Control · Mathematics 2018-11-07 Kanishka Raj Singh , Qiang Shen , Sze Zheng Yong

The methods of approximation, regularization and smoothing of trigonometric interpolation splines are considered in the paper. It is shown that trigonometric splines can be considered from two points of view - as a trigonometric Fourier…

Numerical Analysis · Mathematics 2021-03-23 V. Denysiuk

We consider the problem of model reduction of parametrized PDEs where the goal is to approximate any function belonging to the set of solutions at a reduced computational cost. For this, the bottom line of most strategies has so far been…

Numerical Analysis · Mathematics 2020-03-02 V. Ehrlacher , D. Lombardi , O. Mula , F. -X. Vialard
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