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Related papers: Wavelets and framelets from dual pseudo splines

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In this article, we construct two-dimensional integrable and superintegrable sys- tems in terms of the master function formalism and relate them to Mielnik;s and Marquette;s construction in supersymmetric quantum mechanics. For two diferent…

Mathematical Physics · Physics 2017-10-13 Z. Alizadeh , H. Panahi

In this paper, we investigate $C^2$ super-smoothness of the full $C^1$ cubic spline space on a Powell-Sabin refined triangulation, for which a B-spline basis can be constructed. Blossoming is used to identify the $C^2$ smoothness conditions…

Numerical Analysis · Mathematics 2024-11-11 Jan Grošelj , Hendrik Speleers

We present a novel method named truncated hierarchical unstructured splines (THU-splines) that supports both local $h$-refinement and unstructured quadrilateral meshes. In a THU-spline construction, an unstructured quadrilateral mesh is…

Numerical Analysis · Mathematics 2021-04-13 Xiaodong Wei

As is known, any realization of SU(2) in the phase space of a dynamical system can be generalized to accommodate the exceptional supergroup $D(2,1;\alpha)$, which is the most general $\mathcal{N}{=}\,4$ supersymmetric extension of the…

High Energy Physics - Theory · Physics 2019-03-27 Anton Galajinsky , Olaf Lechtenfeld

This work introduces Bilinear Classes, a new structural framework, which permit generalization in reinforcement learning in a wide variety of settings through the use of function approximation. The framework incorporates nearly all existing…

Machine Learning · Computer Science 2021-07-13 Simon S. Du , Sham M. Kakade , Jason D. Lee , Shachar Lovett , Gaurav Mahajan , Wen Sun , Ruosong Wang

Comparing with univariate framelets, the main challenge involved in studying multivariate framelets is that we have to deal with the highly non-trivial problem of factorizing multivariate polynomial matrices. As a consequence, multivariate…

Functional Analysis · Mathematics 2020-10-14 Ran Lu

We present a new refinement strategy for locally refined B-splines which ensures the local linear independence of the basis functions. The strategy also guarantees the spanning of the full spline space on the underlying locally refined…

Numerical Analysis · Mathematics 2022-03-28 Francesco Patrizi

Recently, shearlet systems were introduced as a means to derive efficient encoding methodologies for anisotropic features in 2-dimensional data with a unified treatment of the continuum and digital setting. However, only very few…

Functional Analysis · Mathematics 2010-02-16 P. Kittipoom , G. Kutyniok , W. Lim

In areas such as kernel smoothing and non-parametric regression there is emphasis on smooth interpolation and smooth statistical models. Splines are known to have optimal smoothness properties in one and higher dimensions. It is shown, with…

Computation · Statistics 2008-09-29 Ron A. Bates , Hugo Maruri-Aguilar , Henry P. Wynn

Approximating data points in three or higher dimension space based on cubic B-spline curve is presented. Representations for planar curves, are merged and extended to the higher dimension. The curve is fitted to the order of data points, or…

Graphics · Computer Science 2020-05-19 Debashis Mukherjee

This paper proposes a strategy to solve the problems of the conventional s-version of finite element method (SFEM) fundamentally. Because SFEM can reasonably model an analytical domain by superimposing meshes with different spatial…

Numerical Analysis · Mathematics 2023-10-09 Nozomi Magome , Naoki Morita , Shigeki Kaneko , Naoto Mitsume

This paper proposes a novel framework for the approximation and analysis of circular density data using compositional periodic splines within Bayes spaces with the Hilbert space structure. By applying the centered log-ratio transformation,…

Methodology · Statistics 2026-05-19 Jitka Machalová , Jana Heckenbergerová , Karel Hron

Fusion frames are a convenient tool in applications where we deal with a large amount of data or when a combination of local data is needed. Oblique dual fusion frames are suitable in situations where the analysis for the data and its…

Functional Analysis · Mathematics 2024-01-31 Jorge P. Díaz , Sigrid B. Heineken , Patricia M. Morillas

In this paper we present an efficient and robust approach to compute a normalized B-spline-like basis for spline spaces with pieces drawn from extended Tchebycheff spaces. The extended Tchebycheff spaces and their dimensions are allowed to…

Numerical Analysis · Mathematics 2020-12-08 Rene R. Hiemstra , Thomas J. R. Hughes , Carla Manni , Hendrik Speleers , Deepesh Toshniwal

This paper investigates two important analytical properties of hyperbolic-polynomial penalized splines, HP-splines for short. HP-splines, obtained by combining a special type of difference penalty with hyperbolic-polynomial B-splines…

Numerical Analysis · Mathematics 2022-02-15 Rosanna Campagna , Costanza Conti

We consider a class of sparsity-inducing regularization terms based on submodular functions. While previous work has focused on non-decreasing functions, we explore symmetric submodular functions and their \lova extensions. We show that the…

Machine Learning · Computer Science 2011-06-13 Francis Bach

A new representation of splines that targets efficiency in the analysis of functional data is implemented. The efficiency is achieved through two novel features: using the recently introduced orthonormal spline bases, the so-called {\it…

Computation · Statistics 2024-09-30 Krzysztof Podgórski

Inspired by the work of Hedenmalm, Lindqvist and Seip, we consider different properties of dilations systems of a fixed function $\varphi \in L^2(0,1)$. More precisely, we study when the system $\{\varphi(nx)\}_n$ is a Bessel sequence, a…

Functional Analysis · Mathematics 2021-10-18 Jorge Antezana , Daniel Carando , Melisa Scotti

Dielectric microspheres with diameters on the order of several wavelengths of light have attracted increasing attention from the photonics community due to their ability to produce extraordinarily tightly focused beams termed photonic…

Optics · Physics 2015-03-12 Kenneth W. Allen

In this paper, we overview one promising avenue of progress at the mathematical foundation of deep learning: the connection between deep networks and function approximation by affine splines (continuous piecewise linear functions in…

Machine Learning · Computer Science 2025-01-16 Randall Balestriero , Ahmed Imtiaz Humayun , Richard Baraniuk