What I'm familiar with is described here: http://neuron.eng.wayne.edu/tarek/MITbook/chap2/2_3.html http://neuron.eng.wayne.edu/tarek/MITbook/chap2/2_3.html Bas

What I'm familiar with is described here: http://neuron.eng.wayne.edu/tarek/MITbook/chap2/2_3.html http://neuron.eng.wayne.edu/tarek/MITbook/chap2/2_3.html Basically, one hidden layer networks are already universal approximator; however, it's a nonconstructive result. This article is semi-constructive, - they train more complicated model, then emulate it with a simpler model, but do not know how to train the simple model directly.