Curve and Surface Fitting with Splines

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Overview

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.

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Product Details

Meet the Author

Katholieke Universiteit Leuven
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Table of Contents

Preface
List of Figures
List of Tables
Pt. I Spline Functions
1 Univariate Splines 3
2 Bivariate Splines 23
Pt. II Curve Fitting
3 Curve Fitting: An Introduction 43
4 Least-Squares Spline Curve Fitting 53
5 Smoothing Spline Curve Fitting 75
6 More Smoothing Spline Curves 95
7 Fitting With Convexity Constraints 119
Pt. III Surface Fitting
8 Surface Fitting: An Introduction 137
9 Scattered Data Surface Fitting 147
10 Mesh Data Surface Fitting 169
11 More Scattered Data Smoothing 197
12 More Mesh Data Smoothing 223
Pt. IV FITPACK
13 Available Software 249
References 271
Index 281
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