The fundamental data structure used by ANNs is the layer, and many interconnected layers make up a complete ANN. A layer can be envisaged as an array of neurons, although the use of the word neuron can be misleading, since there is only a marginal correspondence between human brain neurons and the artificial neurons that make up a layer. Bearing that in mind, we will use the term neuron in what follows. As with any computer processing unit, a neuron is characterized by its inputs and its outputs. In general, a neuron has many inputs and one output value. Each input connection carries a weight, wi.
The following diagram shows a neuron. It is important to note that the activation function, f, is non-linear for anything other than trivial ANNs. A general neuron in the network receives inputs from other neurons and each of these carries a weight, wi, as shown, and the network...
