The implementation of neural network for semiconductor PECVD process
Expert Systems with Applications: An International Journal
Convergent design of piecewise linear neural networks
Neurocomputing
A neural-network approach for an automatic LED inspection system
Expert Systems with Applications: An International Journal
A three-stage integrated approach for assembly sequence planning using neural networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Process parameter optimization for MIMO plastic injection molding via soft computing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Neural networks for event extraction from time series: a back propagation algorithm approach
Future Generation Computer Systems
Complex generalized-mean neuron model and its applications
Applied Soft Computing
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The choice of an optimal neural network design for a given problem is addressed. A relationship between optimal network design and statistical model identification is described. A derivative of Akaike's information criterion (AIC) is given. This modification yields an information statistic which can be used to objectively select a `best' network for binary classification problems. The technique can be extended to problems with an arbitrary number of classes