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 function the output of the neuron. But on Matlab documentation of an activation function I quote:

satlin(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

In machine learning, the sums of each node are weighted, and the sum is passed through a non-linear function known as an activation function or transfer function.

In machine learning, the activation function is used more frequently, while I think "transfer function" is more commonly used in signal processing. So anyone using them as two different terms will have to be clearer.

transfer_function = activation function + output function

A value (signal strength) to verify if the neuron will be activated and then compute an output from it. So the whole process can transfer a signal from one layer to another.

Hope this answer helps you! Study Neural Network Tutorial for more insights on this topic. Machine Learning Online Course would be a relevant subject if one wants to master the course.