202 search results - page 9 / 41 » Learning fault-tolerance in Radial Basis Function Networks |
ICANN
2007
Springer
14 years 1 months ago
2007
Springer
Radial basis function networks (RBF) are efficient general function approximators. They show good generalization performance and they are easy to train. Due to theoretical consider...
SIBGRAPI
2009
IEEE
14 years 2 months ago
2009
IEEE
—We present the Hermite radial basis function (HRBF) implicits method to compute a global implicit function which interpolates scattered multivariate Hermite data (unstructured p...
MCS
2000
Springer
13 years 11 months ago
2000
Springer
We introduce a mechanism for constructing and training a hybrid architecture of projection based units and radial basis functions. In particular, we introduce an optimization sche...
ICANNGA
2007
Springer
14 years 1 months ago
2007
Springer
Rates of approximation by networks with Gaussian RBFs with varying widths are investigated. For certain smooth functions, upper bounds are derived in terms of a Sobolev-equivalent ...
IJCNN
2000
IEEE
13 years 11 months ago
2000
IEEE
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...