This is the first project in the Neurolink™ neural network library. All will be compiled into a single project in the future. This is an SLP(Single Layer Perceptron) which is the most simple kind of neural network. TurLaM-2 will be a lot more complex than this. This learns simple addition. This neural network is going to predict the sum of the input values, and the prediction is the output variable. The difference between the predicted and actual sum of the input values is the #ERROR variable. If the error variable gets near or equal to 0, then it has sucessfully learned addition. Free to use, just put a “powered by @tigerlionwhale ‘s Perceptron Neurolink™.”
@AO-85757 ‘s project PerceptronSim for some debugging. It uses the Perceptron Learning Rule, also known as the Delta Rule.
