21 search results - page 1 / 5 » Input Selection for Radial Basis Function Networks by Constr... |
ICANN
2007
Springer
13 years 10 months ago
2007
Springer
Input selection in the nonlinear function approximation is important and difficult problem. Neural networks provide good generalization in many cases, but their interpretability is...
ISNN
2005
Springer
13 years 9 months ago
2005
Springer
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
ESANN
2008
13 years 5 months ago
2008
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
ESANN
2001
13 years 5 months ago
2001
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
SBRN
1998
IEEE
13 years 8 months ago
1998
IEEE
In this paper we investigate alternative designs of a Radial Basis Function Network acting as classifier in a face recognition system. Input to the RBF network is the projections ...