Smoothing and Multivariate Interpolation with Splines
Author | : T. L. Jordan |
Publisher | : |
Total Pages | : 26 |
Release | : 1965 |
Genre | : Numerical analysis |
ISBN | : |
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Author | : T. L. Jordan |
Publisher | : |
Total Pages | : 26 |
Release | : 1965 |
Genre | : Numerical analysis |
ISBN | : |
Author | : Charles K. Chui |
Publisher | : SIAM |
Total Pages | : 192 |
Release | : 1988-01-01 |
Genre | : Mathematics |
ISBN | : 0898712262 |
Subject of multivariate splines presented from an elementary point of view; includes many open problems.
Author | : C. K. Chui |
Publisher | : Elsevier |
Total Pages | : 346 |
Release | : 2014-05-10 |
Genre | : Mathematics |
ISBN | : 1483271005 |
Topics in Multivariate Approximation contains the proceedings of an international workshop on multivariate approximation held at the University of Chile in Santiago, Chile, on December 15-19, 1986. Leading researchers in the field discussed several problem areas related to multivariate approximation and tackled topics ranging from multivariate splines and fitting of scattered data to tensor approximation methods and multivariate polynomial approximation. Numerical grid generation and finite element methods were also explored, along with constrained interpolation and smoothing. Comprised of 22 chapters, this book first describes the application of Boolean methods of approximation in combination with the theory of right invertible operators to bivariate Fourier expansions. The reader is then introduced to ill-posed problems in multivariate approximation; interpolation of scattered data by radial functions; and shape-preserving surface interpolation. Subsequent chapters focus on approximation by harmonic functions; numerical generation of nested series of general triangular grids; triangulation methods; and inequalities arising from best local approximations in rectangles. A bibliography of multivariate approximation concludes the book. This monograph will be of interest to mathematicians.
Author | : A Ramirez |
Publisher | : |
Total Pages | : 242 |
Release | : 2019-07-24 |
Genre | : |
ISBN | : 9781082263231 |
The Curve Fitting Toolbox software supports these nonparametric fitting methods: -"Interpolation Methods" - Estimate values that lie between known data points.-"Smoothing Splines" - Create a smooth curve through the data. You adjust the level of smoothness by varying a parameter that changes the curve from a least-squares straight-line approximation to a cubic spline interpolant.-"Lowess Smoothing" - Create a smooth surface through the data using locally weighted linear regression to smooth data.Interpolation is a process for estimating values that lie between known data points. There are several interpolation methods: - Linear: Linear interpolation. This method fit a different linear polynomial between each pair of data points for curves, or between sets of three points for surfaces.- Nearest neighbor: Nearest neighbor interpolation. This method sets the value of an interpolated point to the value of the nearest data point. Therefore, this method does not generate any new data points.- Cubic spline: Cubic spline interpolation. This method fit a different cubic polynomial between each pair of data points for curves, or between sets of three points for surfaces.After fitting data with one or more models, you should evaluate the goodness of fit A visual examination of the fitte curve displayed in Curve Fitting app should be your firs step. Beyond that, the toolbox provides these methods to assess goodness of fi for both linear and nonlinear parametric fits-"Goodness-of-Fit Statistics" -"Residual Analysis" -"Confidence and Prediction Bounds" The Curve Fitting Toolbox spline functions are a collection of tools for creating, viewing, and analyzing spline approximations of data. Splines are smooth piecewise polynomials that can be used to represent functions over large intervals, where it would be impractical to use a single approximating polynomial. The spline functionality includes a graphical user interface (GUI) that provides easy access to functions for creating, visualizing, and manipulating splines. The toolbox also contains functions that enable you to evaluate, plot, combine, differentiate and integrate splines. Because all toolbox functions are implemented in the open MATLAB language, you can inspect the algorithms, modify the source code, and create your own custom functions. Key spline features: -GUIs that let you create, view, and manipulate splines and manage and compare spline approximations-Functions for advanced spline operations, including differentiation integration, break/knot manipulation, and optimal knot placement-Support for piecewise polynomial form (ppform) and basis form (B-form) splines-Support for tensor-product splines and rational splines (including NURBS)- Shape-preserving: Piecewise cubic Hermite interpolation (PCHIP). This method preserves monotonicity and the shape of the data. For curves only.- Biharmonic (v4): MATLAB 4 grid data method. For surfaces only.- Thin-plate spline: Thin-plate spline interpolation. This method fit smooth surfaces that also extrapolate well. For surfaces only.If your data is noisy, you might want to fit it using a smoothing spline. Alternatively, you can use one of the smoothing methods. The smoothing spline s is constructed for the specified smoothing parameter p and the specified weights wi.
Author | : Carl de Boor |
Publisher | : Springer |
Total Pages | : 348 |
Release | : 2001-12-01 |
Genre | : Mathematics |
ISBN | : 0387953663 |
This book is based on the author’s experience with calculations involving polynomial splines, presenting those parts of the theory especially useful in calculations and stressing the representation of splines as weighted sums of B-splines. The B-spline theory is developed directly from the recurrence relations without recourse to divided differences. This reprint includes redrawn figures, and most formal statements are accompanied by proofs.
Author | : Borislav D. Bojanov |
Publisher | : Springer Science & Business Media |
Total Pages | : 287 |
Release | : 2013-06-29 |
Genre | : Mathematics |
ISBN | : 940158169X |
Spline functions entered Approximation Theory as solutions of natural extremal problems. A typical example is the problem of drawing a function curve through given n + k points that has a minimal norm of its k-th derivative. Isolated facts about the functions, now called splines, can be found in the papers of L. Euler, A. Lebesgue, G. Birkhoff, J. Favard, L. Tschakaloff. However, the Theory of Spline Functions has developed in the last 30 years by the effort of dozens of mathematicians. Recent fundamental results on multivariate polynomial interpolation and multivari ate splines have initiated a new wave of theoretical investigations and variety of applications. The purpose of this book is to introduce the reader to the theory of spline functions. The emphasis is given to some new developments, such as the general Birkoff's type interpolation, the extremal properties of the splines and their prominant role in the optimal recovery of functions, multivariate interpolation by polynomials and splines. The material presented is based on the lectures of the authors, given to the students at the University of Sofia and Yerevan University during the last 10 years. Some more elementary results are left as excercises and detailed hints are given.
Author | : Anatoly Yu. Bezhaev |
Publisher | : Springer Science & Business Media |
Total Pages | : 291 |
Release | : 2013-04-18 |
Genre | : Mathematics |
ISBN | : 147573428X |
This book is a systematic description of the variational theory of splines in Hilbert spaces. All central aspects are discussed in the general form: existence, uniqueness, characterization via reproducing mappings and kernels, convergence, error estimations, vector and tensor hybrids in splines, dimensional reducing (traces of splines onto manifolds), etc. All considerations are illustrated by practical examples. In every case the numerical algorithms for the construction of splines are demonstrated.
Author | : Paul Dierckx |
Publisher | : Oxford University Press |
Total Pages | : 308 |
Release | : 1995 |
Genre | : Computers |
ISBN | : 9780198534402 |
The fitting of a curve or surface through a set of observational data is a very frequent problem in different disciplines (mathematics, engineering, medicine, ...) with many interesting applications. This book describes the algorithms and mathematical fundamentals of a widely used software package for data fitting with (tensor product) splines. As such it gives a survey of possibilities and benefits but also of the problems to cope with when approximating with this popular type of function. In particular it is demonstrated 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 examples, academic as well as taken from real life.
Author | : J. Braselton |
Publisher | : CreateSpace |
Total Pages | : 114 |
Release | : 2014-09-10 |
Genre | : Mathematics |
ISBN | : 9781502332462 |
Curve Fitting Toolbox provides graphical tools and command-line functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives. The most important topics in this book are: Interactive Spline Fitting Programmatic Spline Fitting Curve Fitting Toolbox Splines MATLAB Splines Expected Background Vector Data Type Support Spline Function Naming Conventions Arguments for Curve Fitting Toolbox Spline Functions Cubic Spline Interpolation Cubic Spline Interpolant of Smooth Data Periodic Data Other End Conditions General Spline Interpolation Knot Choices Smoothing Least Squares Vector-Valued Functions Fitting Values at N-D Grid with Tensor-Product Splines Fitting Values at Scattered 2-D Sites with Thin-Plate Smoothing Splines Postprocessing Splines B-Splines and Smoothing Splines Multivariate and Rational SplinesLeast-Squares Approximation by Natural Cubic Splines Solving A Nonlinear ODE Construction of the Chebyshev Spline Approximation by Tensor Product Splines
Author | : Ren-Hong Wang |
Publisher | : Springer Science & Business Media |
Total Pages | : 522 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 9401723788 |
This book deals with the algebraic geometric method of studying multivariate splines. Topics treated include: the theory of multivariate spline spaces, higher-dimensional splines, rational splines, piecewise algebraic variety (including piecewise algebraic curves and surfaces) and applications in the finite element method and computer-aided geometric design. Many new results are given. Audience: This volume will be of interest to researchers and graduate students whose work involves approximations and expansions, numerical analysis, computational geometry, image processing and CAD/CAM.