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» Functional preprocessing for multilayer perceptrons
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NPL
2006
109views more  NPL 2006»
13 years 7 months ago
CB3: An Adaptive Error Function for Backpropagation Training
Effective backpropagation training of multi-layer perceptrons depends on the incorporation of an appropriate error or objective function. Classification-based (CB) error functions ...
Michael Rimer, Tony Martinez
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 27 days ago
A pareto archive evolutionary strategy based radial basis function neural network training algorithm for failure rate prediction
This paper outlines a radial basis function neural network approach to predict the failures in overhead distribution lines of power delivery systems. The RBF networks are trained ...
Grant Cochenour, Jerad Simon, Sanjoy Das, Anil Pah...
ICA
2004
Springer
14 years 22 days ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela
ICIAP
2005
ACM
14 years 7 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
FLAIRS
2004
13 years 8 months ago
Hidden Layer Training via Hessian Matrix Information
The output weight optimization-hidden weight optimization (OWO-HWO) algorithm for training the multilayer perceptron alternately updates the output weights and the hidden weights....
Changhua Yu, Michael T. Manry, Jiang Li