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2,654,228
Reconstruction and Representation of 3D Objects with Radial Basis Functions
- Computer Graphics (SIGGRAPH ’01 Conf. Proc.), pages 67–76. ACM SIGGRAPH
, 2001
"... We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs al ..."
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Cited by 500 (1 self)
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We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs
On the Integrability of Radial Basis Functions
"... In this paper, we investigate the integrability of certain radial basis functions. From the following forms of function OE, OE(r) = ( P d+[ff] k=0 c k r ff\Gammak + g(r) r ? A; P d+[ff] k=0 c k r ff\Gammak log r + g(r); r ? A; where A 0 and g ffi k \Delta k 2 L 1 (IR d ), we construct the ..."
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In this paper, we investigate the integrability of certain radial basis functions. From the following forms of function OE, OE(r) = ( P d+[ff] k=0 c k r ff\Gammak + g(r) r ? A; P d+[ff] k=0 c k r ff\Gammak log r + g(r); r ? A; where A 0 and g ffi k \Delta k 2 L 1 (IR d ), we construct
On the construction and training of reformulated radial basis function networks
- IEEE Transactions on Neural Networks
, 2003
"... Abstract—This paper presents a systematic approach for constructing reformulated radial basis function (RBF) neural networks, which was developed to facilitate their training by supervised learning algorithms based on gradient descent. This approach reduces the construction of radial basis function ..."
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Cited by 14 (0 self)
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Abstract—This paper presents a systematic approach for constructing reformulated radial basis function (RBF) neural networks, which was developed to facilitate their training by supervised learning algorithms based on gradient descent. This approach reduces the construction of radial basis function
Heterogeneous Radial Basis Function
, 1996
"... This Peer-Reviewed Article is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in All Faculty ..."
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This Peer-Reviewed Article is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in All Faculty
Radial Basis Functions for Process Control
, 1994
"... Radial basis function #RBFs# neural networks provide an attractive method for high dimensional nonparametric estimation for use in nonlinear control. They are faster to train than conventional feedforward networks with sigmoidal activation networks ##backpropagation nets"#, and provide a mod ..."
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Radial basis function #RBFs# neural networks provide an attractive method for high dimensional nonparametric estimation for use in nonlinear control. They are faster to train than conventional feedforward networks with sigmoidal activation networks ##backpropagation nets"#, and provide a
Animated Deformations with Radial Basis Functions
- In ACM Virtual Reality and Software Technology (VRST
, 2000
"... We present a novel approach to creating deformations of polygonal models using Radial Basis Functions (RBFs) to produce localized real-time deformations. Radial Basis Functions assume surface smoothness as a minimal constraint and animations produce smooth displacements of affected vertices in a mod ..."
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Cited by 27 (0 self)
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We present a novel approach to creating deformations of polygonal models using Radial Basis Functions (RBFs) to produce localized real-time deformations. Radial Basis Functions assume surface smoothness as a minimal constraint and animations produce smooth displacements of affected vertices in a
Characterization and construction of radial basis functions
- Multivariate Approximation and Applications
, 2001
"... We review characterizations of (conditional) positive deniteness and show how they apply to the theory of radial basis functions. We then give complete proofs for the (conditional) positive deniteness of all practically relevant basis functions. Furthermore, we show how some of these characterizatio ..."
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Cited by 33 (8 self)
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We review characterizations of (conditional) positive deniteness and show how they apply to the theory of radial basis functions. We then give complete proofs for the (conditional) positive deniteness of all practically relevant basis functions. Furthermore, we show how some
radial basis function networks
, 2005
"... Evolutionary system for automatically constructing and adapting ..."
Results 1 - 10
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2,654,228
