'Single-layer' is an easily overlooked and absolutely essential modifier. Very few networks these days are single layers. (Three is the minimum for infinite dimensional functional approximation, given nonlinear activations.) Deep Networks you see in new research papers these days have, at minimum, perhaps three layers. Some by LeCun et al. will go as high as nine or twelve layers, with four or sixteen layers in breadth.