RBF Neural Network traning data limit

I'm new to RBF Neural Networks and I'm facing the following issue: in designing a rbf nn for forecasting a variable dependent by two inputs variables , if the traning data set excede 4000 samples, at least using Matlab newrbe function, I'm not able to get a result as Matlab stop responding and also hangs my computer (cpu utilization reaches 90% and memory utilization almost fill all available ram). I wonder if this is a limitation of RBF NN or a problem to Matlab implementation of RBF NN or ............probably I have committed a design error. Thanks.

Answer 1

[Greg Heath]

Divide your data randomly into n partitions.

Train a successful net for each partition

Average the outputs to form a single net.

Thank you for formally accepting my answer

Greg

P.S. Search the terms network committee and ensemble network