Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Multi-layer perceptrons with B-spline receptive field functions
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Neural Computation
Square Unit Augmented, Radially Extended, Multilayer Perceptrons
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
The Volterra and Wiener Theories of Nonlinear Systems
The Volterra and Wiener Theories of Nonlinear Systems
Ensembles of Learning Machines
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Automatic Model Selection in a Hybrid Perceptron/Radial Network
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Learning Classification RBF Networks by Boosting
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Forward and Backward Selection in Regression Hybrid Network
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
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A hybrid architecture that includes Radial Basis Functions (RBF) and projection based hidden units is introduced together with a simple gradient based training algorithm. Classification and regression results are demonstrated on various data sets and compared with several variants of RBF networks. In particular, best classification results are achieved on the vowel classification data [1].