Results 241 to 250 of about 763,332 (302)

Reconstruction and representation of 3D objects with radial basis functions

International Conference on Computer Graphics and Interactive Techniques, 2001
J. Carr, R. Beatson, J. Cherrie, T. Mitchell, W. R. Fright, B. C. McCallum, T. R. Evans   +6 more
semanticscholar   +1 more source

Radial Basis Function Networks

2018
Radial basis function (RBF) networks represent a fundamentally different architecture from what we have seen in the previous chapters. All the previous chapters use a feed-forward network in which the inputs are transmitted forward from layer to layer in a similar fashion in order to create the final outputs.
openaire   +1 more source

Deformable Radial Basis Functions

2007
Radial basis function networks (RBF) are efficient general function approximators. They show good generalization performance and they are easy to train. Due to theoretical considerations RBFs commonly use Gaussian activation functions. It has been shown that these tight restrictions on the choice of possible activation functions can be relaxed in ...
Wolfgang Hübner, Hanspeter A. Mallot
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Radial Basis Functions Networks

2002
The solution of complex mapping problems with artificial neural networks normally demands the use of a multi-layer network structure. This multi-layer topology process data into consecutive steps in each one of the layers. Radial Basis Functions networks are a particular neural network structure that uses radial functions in the intermediate, or hidden,
A. Braga, A. C. Carvalho, T. Ludermir, M. de Almeida, E. Lacerda   +4 more
openaire   +1 more source

Radial-Basis Function Networks

2000
This chapter deals with a special class of artificial neural networks (ANNs) called radial-basis function (RBF) networks. These networks derive their structure and interpretation from the theory of interpolation in multidimensional spaces, and have a mathematical foundation imbedded in regularization theory for solving ill-conditioned problems.
Rao S. Govindaraju, Bin Zhang
openaire   +1 more source

An 88-line MATLAB code for the parameterized level set method based topology optimization using radial basis functions

Structural And Multidisciplinary Optimization, 2018
P. Wei, Zuyu Li, Xueping Li, M. Wang
semanticscholar   +1 more source

Influence of the Discretization Methods on the Distribution of Relaxation Times Deconvolution: Implementing Radial Basis Functions with DRTtools

, 2015
T. Wan, M. Saccoccio, Chi Chen, F. Ciucci   +3 more
semanticscholar   +1 more source

Multiscale Radial Basis Functions

2017
Radial basis functions (RBFs) are a popular meshfree discretisation method for constructing high-order approximation spaces. They are used in various areas comprising, for example, scattered data approximation, computer graphics, machine learning, aeroelasticity and the geosciences.The approximation space is usually formed using the shifts of a fixed ...
openaire   +1 more source

Epileptic Seizure Classification of EEGs Using Time–Frequency Analysis Based Multiscale Radial Basis Functions

IEEE journal of biomedical and health informatics, 2018
Yang Li, Xudong Wang, Mei-Lin Luo, Ke Li, Xiao-Feng Yang, Qi Guo   +5 more
semanticscholar   +1 more source

Fast Radial Basis Functions for Engineering Applications

, 2018
M. Biancolini
semanticscholar   +1 more source