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Approximating complex curves with simple parametric curves is widely used in CAGD, CG, and CNC. This paper presents an algorithm to compute a certified approximation to a given parametric space curve with cubic B-spline curves. By…

Computational Geometry · Computer Science 2012-03-05 Liyong Shen , Chunming Yuan , Xiao-Shan Gao

Modeling, simulation and visualization of three-dimension complex bodies widely use mathematical model of curves and surfaces. The most important curves and surfaces for these purposes are curves and surfaces in Hermite and Bezier forms,…

Graphics · Computer Science 2007-05-23 Dmitry P. Paukov

In this paper we provide a priori error estimates in standard Sobolev (semi-)norms for approximation in spline spaces of maximal smoothness on arbitrary grids. The error estimates are expressed in terms of a power of the maximal grid…

Numerical Analysis · Mathematics 2019-07-09 Espen Sande , Carla Manni , Hendrik Speleers

Curve-based methods are one of the classic lane detection methods. They learn the holistic representation of lane lines, which is intuitive and concise. However, their performance lags behind the recent state-of-the-art methods due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Haoxin Chen , Mengmeng Wang , Yong Liu

Physics-informed machine learning offers a promising framework for solving complex partial differential equations (PDEs) by integrating observational data with governing physical laws. However, learning PDEs with varying parameters and…

Machine Learning · Computer Science 2026-03-17 Zhuoyuan Wang , Raffaele Romagnoli , Saviz Mowlavi , Yorie Nakahira

In recent publications, the author and his coworkers have shown robust approximation error estimates for B-splines of maximum smoothness and have proposed multigrid methods based on them. These methods allow to solve the linear system…

Numerical Analysis · Mathematics 2021-03-05 Stefan Takacs

In this work, we present some new integration formulas for any order of accuracy as an application of the B-spline relations obtained in [1]. The resulting rules are defined as a perturbation of the trapezoidal integration method. We prove…

Numerical Analysis · Mathematics 2024-05-21 Dionisio F. Yáñez

This paper deals with the following important research question. Traditionally, the neural network employs non-linear activation functions concatenated with linear operators to approximate a given physical phenomenon. They "fill the space"…

Numerical Analysis · Mathematics 2022-01-05 Kamil Doległo , Anna Paszyńska , Maciej Paszyński , Leszek Demkowicz

The property of preserving the convexity and concavity of the Bernstein polynomial and of the B\'{e}zier curves is used to generate a method of approximating the reliability polynomial of a hammock network. The mutual behaviour of the…

Discrete Mathematics · Computer Science 2019-12-09 Gabriela Cristescu , Vlad-Florin Drăgoi

Approximate duals of B-splines were first used by Chui et al. (2004) for the purpose of constructing tight wavelet frames on bounded intervals. They are splines with local support, whose inner product with a polynomial in the spline space…

Numerical Analysis · Mathematics 2025-11-19 Joachim Stöckler

Isogeometric Analysis generalizes classical finite element analysis and intends to integrate it with the field of Computer-Aided Design. A central problem in achieving this objective is the reconstruction of analysis-suitable models from…

Numerical Analysis · Mathematics 2022-11-09 Thomas Takacs , Deepesh Toshniwal

The novel Locally Refined B-spline (LR B-spline) surface format is suited for representing terrain and seabed data in a compact way. It provides an alternative to the well know raster and triangulated surface representations. An LR B-spline…

Numerical Analysis · Mathematics 2021-05-13 Vibeke Skytt , Tor Dokken

This paper approximates simulation models by B-splines with a penalty on high-order finite differences of the coefficients of adjacent B-splines. The penalty prevents overfitting. The simulation output is assumed to be nonnegative. The…

Optimization and Control · Mathematics 2015-06-19 Yu Xia , Farid Alizadeh

Spline functions have long been used in numerical solution of differential equations. Recently it revives as isogeometric analysis, which offers integration of finite element analysis and NURBS based CAD into a single unified process.…

Numerical Analysis · Mathematics 2019-08-08 Guohui Zhao

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

Computing the envelope of deforming planar domains is a significant and challenging problem with a wide range of potential applications. We approximate the envelope using circular arc splines, curves that balance geometric flexibility and…

Computational Geometry · Computer Science 2025-12-01 Jana Vráblíková , Bert Jüttler

Spline functions have long been used in numerical solution of differential equations. Recently it revives as isogeometric analysis, which offers integration of finite element analysis and NURBS based CAD into a single unified process.…

Numerical Analysis · Mathematics 2019-08-08 Guohui Zhao

We used a collocation method in refinable spline space to solve a linear dynamical system having fractional derivative in time. The method takes advantage of an explicit derivation rule for the B-spline basis that allows us to efficiently…

Numerical Analysis · Mathematics 2020-08-03 Enza Pellegrino , Laura Pezza , Francesca Pitolli

We introduce an efficient algorithmic procedure for implementing the direct formula that represents the product of splines in the B-spline basis. We first demonstrate the relevance of this direct approach through numerical evidence showing…

Numerical Analysis · Mathematics 2026-05-14 Francesco Patrizi , Alessandra Sestini

Fitting B-splines to discrete data is especially challenging when the given data contain noise, jumps, or corners. Here, we describe how periodic data sets with these features can be efficiently and robustly approximated with B-splines by…

Numerical Analysis · Mathematics 2020-12-09 David Lenz , Oana Marin , Vijay Mahadevan , Raine Yeh , Tom Peterka