# Does Deep network (e.g. # of hidden layer=2) always better than shallow network (i.e. # of hidden layer=1)?

I attempted to build a deep network (e.g. deep autoencoder) for some object classification, my result showed that the deep networks is worst than shallow network. However, from what I have read from lecture, deep network perform well. This raise me a question: does deep always better than shallow? If not, in what situation?

Is that any existing problem (published) showing that a shallow network is better than a deep network?