Feedforward networks with one hidden layer and their rates of approximation

We present an overview of some rates of approximation with respect to various computational units in the hidden layer of a one-layered feedforward neural network. The problem of estimating the number of units in the hidden layer is examined to ensure a given degree of approximation for a given function class. The results are discussed in terms of their complexity and functional characteristics.