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Radial basis function

Known as: Basis, RBF, Radial basis functions 
A radial basis function (RBF) is a real-valued function whose value depends only on the distance from the origin, so that ; or alternatively on the… Expand
Wikipedia

Related topics

Related topics

32 relations
Activation functionArtificial neural networkBasis functionBoundary element method
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Broader (2)

InterpolationNumerical analysis

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2009
Highly Cited
2009
Radial Basis Functions - Theory and Implementations
  • M. Buhmann
  • Cambridge monographs on applied and computational…
  • 2009
    • Corpus ID: 122445786
Preface 1. Introduction 2. Summary of methods and applications 3. General methods for approximation and interpolation 4. Radial… Expand
Highly Cited
2002
Highly Cited
2002
A point interpolation meshless method based on radial basis functions
A point interpolation meshless method is proposed based on combining radial and polynomial basis functions. Involvement of radial… Expand
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Highly Cited
2001
Highly Cited
2001
Reconstruction and representation of 3D objects with radial basis functions
We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair… Expand
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Highly Cited
2001
Highly Cited
2001
A Radial Basis Function Method for Global Optimization
AbstractWe introduce a method that aims to find the global minimum of a continuous nonconvex function on a compact subset of… Expand
Review
2000
Review
2000
Radial basis functions
Radial basis function methods are modern ways to approximate multivariate functions, especially in the absence of grid data. They… Expand
Highly Cited
1999
Highly Cited
1999
An algorithm for selecting a good value for the parameter c in radial basis function interpolation
  • S. Rippa
  • Adv. Comput. Math.
  • 1999
    • Corpus ID: 3330803
The accuracy of many schemes for interpolating scattered data with radial basis functions depends on a shape parameter c of the… Expand
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Highly Cited
1998
Highly Cited
1998
Solving partial differential equations by collocation using radial basis functions
After a series of application papers have proven the approach to be numerically effective, this paper gives the first theoretical… Expand
Highly Cited
1995
Highly Cited
1995
Error estimates and condition numbers for radial basis function interpolation
For interpolation of scattered multivariate data by radial basis functions, an “uncertainty relation” between the attainable… Expand
Highly Cited
1993
Highly Cited
1993
Approximation and Radial-Basis-Function Networks
This paper concerns conditions for the approximation of functions in certain general spaces using radial-basis-function networks… Expand
Highly Cited
1988
Highly Cited
1988
Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks
Abstract : The relationship between 'learning' in adaptive layered networks and the fitting of data with high dimensional… Expand
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