Φ(x1, x2, … xn)
...
x1
xn
x2
activation function
Φ
The input signals get multiplied by weight values. We can see all the inputs as an input vector and the corresponding weights as the weights vector.
When a signal comes in, it gets multiplied by a weight value that is assigned to this particular input. That is, if a neuron has three inputs, then it has three weights that can be adjusted individually. The weights usually get adjusted during the learn phase.
The modified input signals are summed up. We can optionally add a bias value b to this sum. The bias is a value which can also be adjusted during the learn phase.
Finally, the actual output has to be determined. For this purpose an activation or step function Φ is used.