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In this paper, we address the problem of constructing $C^2$ cubic spline functions on a given arbitrary triangulation $\mathcal{T}$. To this end, we endow every triangle of $\mathcal{T}$ with a Wang-Shi macro-structure. The $C^2$ cubic…

Numerical Analysis · Mathematics 2023-07-28 Tom Lyche , Carla Manni , Hendrik Speleers

In this work, we Extend Pawlak approximation spaces by topological spaces. Also, Rough Membership, equality and inclusion relations are extended using topological near open sets. In addition, new extended measures of accuracy and quality of…

General Topology · Mathematics 2019-08-19 A. S. Salama , O. G. Elbarbary

A fast algorithm for B-splines in mixed models is presented. B-splines have local support and are computational attractive, because the corresponding matrices are sparse. A key element of the new algorithm is that the local character of…

Computation · Statistics 2015-02-17 Martin P. Boer

In this work, we propose a convenient framework for infinite-dimensional analysis (including both real and complex analysis in infinite dimensions), in which differentiation (in some weak sense) and integration operations can be easily…

Functional Analysis · Mathematics 2024-12-03 Jiayang Yu , Xu Zhang

Analysis-suitable $G^1$ (AS-$G^1$) multi-patch spline surfaces [4] are particular $G^1$-smooth multi-patch spline surfaces, which are needed to ensure the construction of $C^1$-smooth multi-patch spline spaces with optimal polynomial…

Numerical Analysis · Mathematics 2023-12-25 Andrea Farahat , Mario Kapl , Aljaž Kosmač , Vito Vitrih

We consider several characterizations of $\mathbb R$-linear mappings. In particular, we give a characterization of linear mappings whose range is $\geq$ 2 dimensional, in terms of preservation of lines (and contraction of lines to a point)…

General Mathematics · Mathematics 2020-08-06 Sakaé Fuchino

Unmeasured, spatially-structured factors can confound associations between spatial environmental exposures and health outcomes. Adding flexible splines to a regression model is a simple approach for spatial confounding adjustment, but the…

Applications · Statistics 2020-06-22 Joshua P. Keller , Adam A. Szpiro

Multi-degree splines are smooth piecewise-polynomial functions where the pieces can have different degrees. We describe a simple algorithmic construction of a set of basis functions for the space of multi-degree splines, with similar…

Numerical Analysis · Mathematics 2021-10-19 Hendrik Speleers

Periodic splines are a special kind of splines that are defined over a set of knots over a circle and are adequate for solving interpolation problems related to closed curves. This paper presents a method of implementing the objects…

Numerical Analysis · Mathematics 2023-02-16 Hiba Nassar , Krzysztof Podgórski

This paper considers the development of spatially adaptive smoothing splines for the estimation of a regression function with non-homogeneous smoothness across the domain. Two challenging issues that arise in this context are the evaluation…

Statistics Theory · Mathematics 2013-06-11 Xiao Wang , Pang Du , Jinglai Shen

The smooth piecewise-linear models cover a wide range of applications nowadays. Basically, there are two classes of them: models are transitional or hyperbolic according to their behaviour at the phase-transition zones. This study explored…

Methodology · Statistics 2020-11-17 Ferreira , Iuri Emmanuel de Paula , Zocchi , Silvio Sandoval

Dual pseudo splines constitute a new class of refinable functions with B-splines as special examples, which was introduced in \cite{DHSS}. In this paper, we shall construct Riesz wavelet associated with dual pseudo splines. Furthermore, we…

Functional Analysis · Mathematics 2015-05-19 Yi Shen , Song Li

We extend the adaptive regression spline model by incorporating saturation, the natural requirement that a function extend as a constant outside a certain range. We fit saturating splines to data using a convex optimization problem over a…

Machine Learning · Statistics 2017-12-05 Nicholas Boyd , Trevor Hastie , Stephen Boyd , Benjamin Recht , Michael Jordan

In this paper, the reachability of dimension-bounded linear systems is investigated.Since state dimensions of dimension-bounded linear systems vary with time, the expression of state dimension at each time is provided.A method for judging…

Systems and Control · Electrical Eng. & Systems 2021-09-21 Yiliang Li , Haitao Li , Jun-e Feng , Jinjin Li

This paper surveys recent developments in the sampling discretization of integral and uniform norms for functions in general finite-dimensional spaces. These results generalize the classical Marcinkiewicz-Zygmund inequalities for…

Numerical Analysis · Mathematics 2026-03-04 F. Dai , E. Kosov , V. Temlyakov

We present large sample results for partitioning-based least squares nonparametric regression, a popular method for approximating conditional expectation functions in statistics, econometrics, and machine learning. First, we obtain a…

Statistics Theory · Mathematics 2020-07-20 Matias D. Cattaneo , Max H. Farrell , Yingjie Feng

We study the rational approximation properties of special manifolds defined by a set of polynomials with rational coefficients. Mostly we will assume the case of all polynomials to depend on only one variable. In this case the manifold can…

Number Theory · Mathematics 2018-12-31 Johannes Schleischitz

Much like admissibility is the key concept underlying preferred semantics, strong admissibility is the key concept underlying grounded semantics, as membership of a strongly admissible set is sufficient to show membership of the grounded…

Artificial Intelligence · Computer Science 2022-04-08 Martin Caminada , Sri Harikrishnan

This paper presents an enhanced version of our previous work, hybrid non-uniform subdivision surfaces [19], to achieve optimal convergence rates in isogeometric analysis. We introduce a parameter $\lambda$ ($\frac{1}{4}<\lambda<1$) to…

Numerical Analysis · Mathematics 2020-03-30 Xiaodong Wei , Xin Li , Yongjie Jessica Zhang , Thomas J. R. Hughes

In this paper, we study a part of approximation theory that presents the conditions under which a closed set in a normed linear space is proximinal or Chebyshev.

Functional Analysis · Mathematics 2011-12-30 Hadi Haghshenas
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