Neural Network Toolbox

Weight Blocks

Double-click on the Weight Functions block in the Neural window to bring up a window containing three weight function blocks.

Each of these blocks takes a neuron's weight vector and applies it to an input vector (or a layer output vector) to get a weighted input value for a neuron.

It is important to note that the blocks above expect the neuron's weight vector to be defined as a column vector. This is because Simulink signals can be column vectors, but cannot be matrices or row vectors.

It is also important to note that because of this limitation you have to create S weight function blocks (one for each row), to implement a weight matrix going to a layer with S neurons.

This contrasts with the other two kinds of blocks. Only one net input function and one transfer function block are required for each layer.

Net Input Blocks

Control Systems Blocks