An example maybe ? Let's say I want to approximate a 2-parameters (x and y) function with a single node.
So I have to add a third component to the input set to 1.0
Then the node has 2+1 inputs (so 3 weights too) and the input vector is [1.0,x,y]
So the integration is W0*1+W1*x+W2*y

So the code of a node 'without bias' is perfect : just add an extra 1.0 to its input and it's done, you have a node with a bias.

First I have to nuance my statement : you must add a 1.0 component tothe input of any node input ( and not to the net input only as i too quickly said. Sorry).

An example maybe ? Let's say I want to approximate a 2-parameters (x and y) function with a single node.
So I have to add a third component to the input set to 1.0
Then the node has 2+1 inputs (so 3 weights too) and the input vector is [1.0,x,y]
So the integration is W0*1+W1*x+W2*y

So the code of a node 'without bias' is perfect : just add an extra 1.0 to its input and it's done, you have a node with a bias.