C="Neural Net Xor example for the Probabalistic method.
To start training the net, select Simulate/Go from the menu above. The simulation is set to go 4 steps, counting to 3 in binary as training input to the net. When the simulation is finished, click the right mouse button over the xorgr.net block, and turn off \"Learn\". Click on OK, and rerun the simulation. You will see the learned xor results come out of xorgr.net, and see the difference between the neural net results and the builtin xor operator results in VisSim in the upper plot.
The Probablistic method is a discrete, integer valued output classification network. It produces an integer that corresponds to the learned output for a given input. The smoothing factor controls how well the network can generalize new input pattern to trained input patterns. Higher smoothing values result in greater generalization."
