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Highly Cited

2009

Highly Cited

2009

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 is proposed based on combining radial and polynomial basis functions. Involvement of radial… Expand

Highly Cited

2001

Highly Cited

2001

We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair… Expand

Highly Cited

2001

Highly Cited

2001

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 function methods are modern ways to approximate multivariate functions, especially in the absence of grid data. They… Expand

Highly Cited

1999

Highly Cited

1999

The accuracy of many schemes for interpolating scattered data with radial basis functions depends on a shape parameter c of the… Expand

Highly Cited

1998

Highly Cited

1998

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

For interpolation of scattered multivariate data by radial basis functions, an “uncertainty relation” between the attainable… Expand

Highly Cited

1993

Highly Cited

1993

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

Abstract : The relationship between 'learning' in adaptive layered networks and the fitting of data with high dimensional… Expand