How should a neural network for unbound function approximation be structured?
This does not answere your question directly, but might include some helpful pointers:
In the recent Deep Residual Learning for Image Recognition paper it is written:

If one hypothesizes that multiple nonlinear layers can asymptotically
approximate complicated functions[...]
This hypothesis, however, is still an open question. See [28].