Figure 24.5. Components of a feed-forward artificial neural network. The
organisation of nodes in a three-layer artificial neural network (left) where the node in
each layer is connected to all the nodes in the next layer, albeit with different connection
strengths. The hyperbolic tangent is often used as a trigger function to modulate each
node’s output (right). For the trigger function the x axis corresponds to the total input,
which is the weighted sum of the inputs from all the connections. The y axis represents the
node output that may be sent to the next layer.
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