Curve and Surface Fitting with Splines

Paul Dierckx

302 pages, parution le 27/04/1995

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Résumé

The fitting of a curve or surface through a set of observational data is a recurring problem across numerous disciplines such as applications. This book describes the algorithms and mathematical fundamentals of a widely used software package for data fitting with tensor product splines. It gives a survey of possibilities, benefits, and problems commonly confronted when approximating with this popular type of function. Dierkx demonstrates in detail how the properties of B -splines can be fully exploited for improving the computational efficiency and for incorporating different boundary or shape preserving constraints. Special attention is also paid to strategies for an automatic and adaptive knot selection with intent to obtain serious data reductions. The practical use of the smoothing software is illustrated with many theoretical and practical examples.

Sommaire

Spline Functions
- Univariate Splines
- Bivariate Splines
Curve Fitting
- Curve Fitting: An Introduction
- Least-Squares Spline Curve Fitting
- Smoothing Spline Curve Fitting
- More Smoothing Spline Curves
- Fitting with Convexity Constraints
Surface Fitting
- Surface Fitting: An Introduction
- Scattered Data Surface Fitting
- Mesh Data Surface Fitting
- More Scattered Data Smoothing
- More Mesh Data Smoothing
Fitpack
- Available Software

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Oxford University Press
Auteur(s)	Paul Dierckx
Parution	27/04/1995
Nb. de pages	302
Couverture	Relié
Poids	470g
Intérieur	Noir et Blanc
EAN13	9780198534402
ISBN13	9780198534402