RM rbf+ : Advanced Radial Basis Function Technique
Radial basis function (RBF)-based interpolation and spreading for the immersed boundary method
... a radial basis functions frame- work for the spreading-interpolation ...The radial basis function approach allows for dealing with a cloud of scattered nodes around the im- mersed ...
29
Radial basis function (RBF)-based interpolation and spreading for the immersed boundary method
... Copyright and reuse: City Research Online aims to make research outputs of City, University of London available to a wider audience.. Copyright and Moral Rights remain with the author([r] ...
6
An Optimal Radial Basis Function (RBF) Neural Network for Hyper-surface Reconstruction
... Optimal Radial Basis Function (RBF) Neural Network for Hyper-Surface Reconstruction ...a function of both regularization levels and isotropic ...
13
Multilingual Speech Recognition Using Radial Basis Function (RBF) Neural Network
... the function approximation and pattern ...Activation function to calculate the output response of the ...the Radial Basis Function Network shown in Fig-5 , it made up of three layers ...
7
Radial Basis Function (RBF) Neural Network for Load Forecasting during Holiday
... Most of the proposed methods have investigated the weather and environmental factors as the most influential factors affecting the future load profile. Taylor introduced the triple seasonal methods for online short-term ...
5
Radial basis function (RBF)-based interpolation and spreading for the immersed boundary method
... 1. Introduction When considering complex geometries, immersed boundary (IB) methods constitute an efficient alternative to avoid either difficult or even impossible grid generation procedures when dealing with ...
29
A Radial Basis Function (RBF) Compact Finite Difference (FD) Scheme for Reaction-Diffusion Equations on Surfaces
... The goal of HFD methods is to solve a given PDE numerically by computing more accurate approximations to the differential operators in the PDE. In these schemes, this improved accuracy is obtained by using additional ...
24
The Matlab Radial Basis Function Toolbox
... cause RBF matrices to have a structure that allows for substantial saving in storage requirements and reduc- tions in flop counts for associated linear algebra rou- ...
10
Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF) neural networks
... Rosman [9] conducted experimental researches to find precise design data for gas e liquid equilibrium in the water- TEG-methane settings. Equilibrium data, which were measured for high concentrations of TEG differ ...
8
A High-Order Radial Basis Function (RBF) Leray Projection Method for the Solution of the Incompressible Unsteady Stokes Equations
... eralized RBF interpolation with matrix-valued ...the technique of [18] here so that Π also incorporates tangential boundary conditions, unlike both the traditional Leray projector and the implicit Leray ...
35
Adaptive Radial Basis Function Detector for Beamforming
... symmetric radial basis function (RBF) detector is proposed and two adaptive algorithms are developed for training the proposed RBF ...density function while the second algorithm ...
6
Adaptive Radial Basis Function Detector for Beamforming
... ❏ Existing beamforming techniques are linear , and classical beamforming technique is based on minimum mean square error (L-MMSE). ❏ State-of-the-art for linear beamforming is minimum bi[r] ...
20
Symmetric Radial Basis Function Network Equaliser
... By explicitly exploiting the inherently symmetric struc- ture of the optimal Bayesian equaliser, the proposed sym- metric RBF equaliser can be determined from the re- ceived noisy training data. Both a block-data ...
5
Symmetric Radial Basis Function Network Equaliser
... ✰ Which exploits prior knowledge on symmetry property of optimal solution, leading to enhanced performance. ❏ Adaptive algorithms for training this symmetric RBF equaliser have been revi[r] ...
19
Radial Basis Function Assisted Turbo Equalization
... the RBF equalizer in order to reduce its computational complexity via subset center selec- ...the RBF decision-feedback equalizer (DFE) in computing the decision variable of (4) with the additional in- ...
12
Compactly Supported Radial Basis Function Kernels
... We suggest a unified framework to balance the efficiency gain and information loss due to the sparsifying operation, which provides an adaptive tuning approach for the thresholding parameter. In theory, it is required ...
19
Radial Basis Function Neural Networks : A Review
... Radial Basis Function neural networks (RBFNNs) represent an attractive alternative to other neural network ...between function approximation, regularization, noisy interpolation, ...
23
Function Approximation Using Robust Radial Basis Function Networks
... in radial basis function (RBF) networks is the topic of this ...of function approximation, system identification and control is ...
9
A meshless technique based on integrated radial basis function networks for elliptic partial differential equations
... meshless technique based on integrated radial basis function networks (RBFNs) for solving second- and fourth-order elliptic partial differential equations ...approximate function and ...
12
Approximation of function and its derivatives using radial basis function networks
... nite basis and all derivatives are obtained as a ...nite basis. Lower derivatives and nally the function itself are obtained by integration which has the prop- erty of damping out or at least ...
48