Neural network: activation function vs transfer function

Question

It seems there is a bit of confusion between activation and transfer function. From Wikipedia ANN:

It seems that the transfer function calculates the net while the activation functions the output of the neuron. But on Matlab documentation of an activation function I quote:

Stalin(N, FP) is a neural transfer function. Transfer functions calculate a layer's output from its net input.

So who is right? And can you use the term activation function or transfer function interchangeably?

Answer 1

The activation function is the one who decides whether a neuron should be activated or not by calculating a weighted sum and further adding bias with it. The purpose of the activation function is to introduce non-linearity into the output of a neuron.

Transfer function comes from the name transformation and is used for transformation purposes i.e. from input nodes to the output of a neuron. On the other hand, activation function checks for the output if it meets a certain threshold and either outputs zero or one.

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