Results 261 to 270 of about 388,592 (291)
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2017
In this chapter the RBF mathematical concepts are exposed considering firstly the interpolation problem with the RBF function defined by known values at source points; a first hands-on example is provided showing how RBF work. Further topics of RBF theory are then introduced considering the differentiation of RBF, the fitting of an RBF with known ...
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In this chapter the RBF mathematical concepts are exposed considering firstly the interpolation problem with the RBF function defined by known values at source points; a first hands-on example is provided showing how RBF work. Further topics of RBF theory are then introduced considering the differentiation of RBF, the fitting of an RBF with known ...
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Computationally Efficient Radial Basis Function
2018We introduced a Square-law based RBF kernel called SQuare RBF (SQ-RBF) which is computationally efficient and effective due to the elimination of the exponential term. In contrast to the Gaussian RBF, SQ-RBF requires smaller computational operation count and direct implementation without a call to higher order library.
Adedamola Wuraola, Nitish D. Patel
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2004
Radial basis functions are traditionaland powerful tools for multivariate scattered data interpolation.Much of the material presented in this chapter is essentially needed in the subsequent developments of this work,such as for the multi level approximation schemes in Chapter 5, and the mesh free simulation of transport processes in Chapter 6.
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Radial basis functions are traditionaland powerful tools for multivariate scattered data interpolation.Much of the material presented in this chapter is essentially needed in the subsequent developments of this work,such as for the multi level approximation schemes in Chapter 5, and the mesh free simulation of transport processes in Chapter 6.
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Indexed families of functionals, and Gaussian radial basis functions
The 2002 45th Midwest Symposium on Circuits and Systems, 2002. MWSCAS-2002., 2003We report on results concerning the capabilities of gaussian radial basis function networks in the setting of inner product spaces that need not be finite dimensional. Specifically, we show that important indexed families of functionals can be uniformly approximated, with the approximation uniform also with respect to the index.
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Experiments on Ensembles of Radial Basis Functions
2004Building an ensemble of classifiers is an useful way to improve the performance. In the case of neural networks the bibliography has centered on the use of Multilayer Feedforward (MF). However, there are other interesting networks like Radial Basis Functions (RBF) that can be used as elements of the ensemble.
Carlos Hernández-Espinosa +2 more
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Radial Basis Functions: A Bayesian Treatment.
1998Item does not contain ...
Barber, D., Schottky, B.
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On Monotonic Radial Basis Function Networks
IEEE Transactions on CyberneticsThis article deals with monotonicity conditions for radial basis function (RBF) networks. Two architectures of RBF networks are considered-1) unnormalized network with a local character of the basis function and 2) a normalized network where the value of RBF is taken relatively with respect to the others.
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Numerical solution of fractional telegraph equation by using radial basis functions
Engineering Analysis With Boundary Elements, 2014Vahid Reza Hosseini, Wen Chen
exaly
Some observations regarding interpolants in the limit of flat radial basis functions
Computers and Mathematics With Applications, 2004Bengt Fornberg, Elisabeth Larsson
exaly