scholarly journals A Cartesian-grid collocation method based on radial-basis-function networks for solving PDEs in irregular domains

2007 ◽  
Vol 23 (5) ◽  
pp. 1192-1210 ◽  
Author(s):  
N. Mai-Duy ◽  
T. Tran-Cong
Keyword(s):  
Radial Basis Function ◽  
Collocation Method ◽  
Basis Function ◽  
Cartesian Grid ◽  
Radial Basis Function Networks ◽  
Irregular Domains ◽  
Radial Basis

A meshless radial basis function based method for modeling dual-phase-lag heat transfer in irregular domains

2021 ◽  
Vol 85 ◽  
pp. 1-17
Author(s):  
Ji Lin ◽  
Hao Yu ◽  
Sergiy Reutskiy ◽  
Yuan Wang
Keyword(s):  
Heat Transfer ◽  
Radial Basis Function ◽  
Basis Function ◽  
Phase Lag ◽  
Dual Phase ◽  
Irregular Domains ◽  
Radial Basis

Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks

2013 ◽  
Vol 40 (5) ◽  
pp. 1599-1608 ◽  
Author(s):  
A.J. Rivera ◽  
B. García-Domingo ◽  
M.J. del Jesus ◽  
J. Aguilera
Keyword(s):  
Radial Basis Function ◽  
Basis Function ◽  
Radial Basis Function Networks ◽  
Photovoltaic Modules ◽  
Radial Basis

Universal Approximation Using Radial-Basis-Function Networks

1991 ◽  
Vol 3 (2) ◽  
pp. 246-257 ◽  
Author(s):  
J. Park ◽  
I. W. Sandberg
Keyword(s):  
Finite Number ◽  
Radial Basis Function ◽  
Basis Function ◽  
Universal Approximation ◽  
Radial Basis Function Networks ◽  
Feedforward Networks ◽  
Rbf Networks ◽  
Smoothing Factor ◽  
Radial Basis ◽  
Hidden Layer

There have been several recent studies concerning feedforward networks and the problem of approximating arbitrary functionals of a finite number of real variables. Some of these studies deal with cases in which the hidden-layer nonlinearity is not a sigmoid. This was motivated by successful applications of feedforward networks with nonsigmoidal hidden-layer units. This paper reports on a related study of radial-basis-function (RBF) networks, and it is proved that RBF networks having one hidden layer are capable of universal approximation. Here the emphasis is on the case of typical RBF networks, and the results show that a certain class of RBF networks with the same smoothing factor in each kernel node is broad enough for universal approximation.

Sign in / Sign up

Export Citation Format

Share Document