Zobrazeno 1 - 10
of 385
pro vyhledávání: '"65d10"'
We consider the problem of finding the ``best'' approximation of an $n$-dimensional probability measure $\rho$ using a measure $\nu$ whose support is parametrized by $f : \mathbb{R}^m \to \mathbb{R}^n$ where $m < n$. We quantify the performance of th
Externí odkaz:
http://arxiv.org/abs/2409.16541
Autor:
Sabuda, Josef
In this work, the concept of Braced Fourier Continuation and Regression (BFCR) is introduced. BFCR is a novel and computationally efficient means of finding nonlinear regressions or trend lines in arbitrary one-dimensional data sets. The Braced Fouri
Externí odkaz:
http://arxiv.org/abs/2405.03180
Autor:
Wilke, Daniel N
Multifidelity surrogate modelling combines data of varying accuracy and cost from different sources. It strategically uses low-fidelity models for rapid evaluations, saving computational resources, and high-fidelity models for detailed refinement. It
Externí odkaz:
http://arxiv.org/abs/2404.14456
Autor:
Guidotti, Patrick
A kernel based method is proposed for the construction of signature (defining) functions of subsets of $\mathbb{R}^d$. The subsets can range from full dimensional manifolds (open subsets) to point clouds (a finite number of points) and include bounde
Externí odkaz:
http://arxiv.org/abs/2404.00427
A Generalized Variable Projection Algorithm for Least Squares Problems in Atmospheric Remote Sensing
Publikováno v:
Mathematics 2023, 11, 2839
This paper presents a solution for efficiently and accurately solving separable least squares problems with multiple datasets. These problems involve determining linear parameters that are specific to each dataset while ensuring that the nonlinear pa
Externí odkaz:
http://arxiv.org/abs/2401.02301
Autor:
Picklo, Matthew J., Ryan, Jennifer K.
In this article we consider the extension of the (L)SIAC-MRA enhancement procedure to nonuniform meshes. We demonstrate that error reduction can be obtained on perturbed quadrilateral and Delaunay meshes, and investigate the effect of limited resolut
Externí odkaz:
http://arxiv.org/abs/2312.14524
Autor:
Hielscher, Ralf, Pöschl, Tim
Publikováno v:
Adv Comput Math 50, 107 (2024)
We revisit the moving least squares (MLS) approximation scheme on the sphere $\mathbb S^{d-1} \subset \mathbb R^d$, where $d>1$. It is well known that using the spherical harmonics up to degree $L \in \mathbb N$ as ansatz space yields for functions i
Externí odkaz:
http://arxiv.org/abs/2310.15570
Autor:
Richardson, Sean
We consider functions $f: \mathbb{Z} \to \mathbb{R}$ and kernels $u: \{-n, \cdots, n\} \to \mathbb{R}$ normalized by $\sum_{\ell = -n}^{n} u(\ell) = 1$, making the convolution $u \ast f$ a "smoother" local average of $f$. We identify which choice of
Externí odkaz:
http://arxiv.org/abs/2310.09713
Publikováno v:
Journal of Computational and Applied Mathematics 443 (2024) 115773
We consider the weighted least squares spline approximation of a noisy dataset. By interpreting the weights as a probability distribution, we maximize the associated entropy subject to the constraint that the mean squared error is prescribed to a des
Externí odkaz:
http://arxiv.org/abs/2309.08792
Autor:
Adeoye, Adeyemi D., Bemporad, Alberto
We introduce a notion of self-concordant smoothing for minimizing the sum of two convex functions, one of which is smooth and the other may be nonsmooth. The key highlight of our approach is in a natural property of the resulting problem's structure
Externí odkaz:
http://arxiv.org/abs/2309.01781