I was given a target function to design a neural network and train: $y = (x_1 \wedge x_2) \vee (x_3 \wedge x_4)$
The number of inputs and outputs seems obvious (4 and 1). And the training data can use a truth table.
However, in order to train it as a multilayer artificial neural network, I need to choose the number of hidden units. May I know where can I find some general guideline for this?