Favier, A. Pinelli, Radial basis function (rbf)-based interpolation and spreading for the immersed boundary method, Comput. Fluids, 105 (2014) 66-75.Toja-Silva F., Favier, J., Pinelli, A.: Radial basis function (RBF)-based interpolation and spreading for the immersed boundary method. ...
Radial basis function (RBF) interpolation is a robust mesh deformation method, which has the main property of interpolating the displacements of mesh boundary points to the internal points through RBF. However, this method is computationally intensive, especially for problems with large number of ...
interpolate N-D scattered data using the radial basis function interpolation method Calling Sequence Parameters Description Examples Compatibility Calling Sequence RadialBasisFunctionInterpolation(points,values) RadialBasisFunctionInterpolation(points,values,rbf,c) f:=RadialBasisFunctionInterpolation(......
However, this approach does not consider the effect of spatial distribution of the calibration data on the interpolation result. This study proposes a new RBF interpolation approach based on the Freedman's RBF interpolation approach, by which the unit basis functions are uniformly populated in the ...
RBFNs were rst introduced by Powell [15–18] to solve the interpolation problem in a multi-dimensional space requiring as many centers as data points. Later Keywords: neural network; radial basis function net- works; multi-criterions optimization; learning; classi ca- tion; clustering; ...
4) radial base interpolation 径向基插值 1. In this paper a method to use radial base interpolation has been proposed to obtain special person s 3D facial mesh throuth special person s front and side image based on generic facial model. 本文提出了一种在通用人脸模型的基础上,依据特定人脸正面...
In many deformation analyses, the partial derivatives at the interpolated scattered data points are required. In this paper, the Gaussian Radial Basis Functions (GRBF) is proposed for the interpolation and differentiation
A modeling method based on the Radial Basis Function(RBF) was set up,in which the output was the test value of high precision instrument and the input was the angle values of sample points. 建立了径向基函数网络模型,以高精度检测仪器的检测值为学习目标,以生成最小映射误差为原则调节网络权因子...
5.5.7Radial basis function networks and PSSM profiles Ou et al. (2008)proposed a method, TMBETADISC-RBF based on radial basis function (RBF) networks andPSSMprofiles for discriminatingOMPs. The main difference between RBF network and neural network is that in RBF network the hidden units...
Most training algorithms for radial basis function (RBF) neural networks start with a predetermined network structure which is chosen either by using a priori knowledge or based on previous experience. The resulting network is often insufficient or unnecessarily complicated and an appropriate network stru...