In this class one layer of neurons is implemented, consisting of a number of neurons and a constant input called bias. The neurons within the layer are of type CCell.
A object of class CLayer can calculate the output of the layer for a given input; this method is used in the working mode of the network as well as during learning. Most other methods in this class implement the BP-learning for one layer. The CLayer-object has methods to calculate the error signal () for a hidden layer and for an output layer. This makes it possible to use the class to implement both types of layers in a MLP.