Deep one-gate per layer networks with skip connections are universal classifiers

Abstract

This paper shows how a multilayer perceptron with two hidden layers, which has been designed to classify two classes of data points, can easily be transformed into a deep neural network with one-gate layers and skip connections.

5 pages, 6 figures