Normalized implicit eigenvector least squares operators for noisy scattered data: Radial basis functions

DOI10.1007/s00607-009-0054-7zbMath1176.65013OpenAlexW2013499046MaRDI QIDQ1034748

Gregory M. Nielson

Publication date: 6 November 2009

Published in: Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00607-009-0054-7

zbMATH Keywords

numerical examplesradial basis functionsscattered data approximationsurface fittingisosurfacespoint cloudsimplicit least squaresnoisy BD data

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Computer-aided design (modeling of curves and surfaces) (65D17)

Cites Work

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• Implicit fitting of point cloud data using radial Hermite basis functions
• Piecewise optimal triangulation for the approximation of scattered data in the plane
• Least squares surface approximation to scattered data using multiquadratic functions
• Smooth interpolation of large sets of scattered data
• Knot Selection for Least Squares Thin Plate Splines
• Three-dimensional alpha shapes
• Meshless parameterization and surface reconstruction

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