I am reading a very interesting paper on genetic algorithms which define neural networks. I am familiar with how a feedforward neural network operates, but then I came across this:
Where node #4 goes back to connect to #5. I was wondering how this is handled? Does the state of node 4 get kept from the last timestep and applied to node 5 when it is time to calculate its activation?