The Neural Network Toolbox is written so that if you read Chapter 2, Chapter
3 and Chapter 4 you can proceed to a later chapter, read it and use its functions
without difficulty. To make this possible, Chapter 2 presents the fundamentals
of the neuron model,
the architectures of neural networks. It also will discuss
notation used in the architectures. All of this is basic material. It is to your
advantage to understand this Chapter 2 material thoroughly.
The neuron model and the architecture of a neural network describe how a
network transforms its input into an output. This transformation can be
viewed as a computation. The model and the architecture each place
limitations on what a particular neural network can compute. The way a
network computes its output must be understood before training methods for
the network can be explained.