I1 and I2 are the inputs scaled to [-1,1] or [0, 1], depending on the activation function usedf()=Activation Function=Tanh(), Sigmoid() or any differential-able function
W=Current neurons input weights, initialized randomly between [-1, 1].
Wb=Bias Weight, connected to nothing, used as a threshold, initialized same as W
N=The output of the current neuron.
O=Output Neurons Previous Output
E=Error for Current Neuron
T=Output Neurons Desired Output.
f’(N) is the derivative of the activation function, N is the Neurons previous output.