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?
In engineering, a transfer function (also known as system function or network function) of a system, sub-system, or component is a mathematical function that theoretically models the system's output for each possible input. They are widely used in electronics and control systems.
The transfer function translates the input signals to output signals. Four types of transfer functions are commonly used, Unit step (threshold), sigmoid, piecewise linear, and Gaussian. Unit step (threshold)
Different activation functions allow for different non-linearities which might work better for solving a specific function. Using a sigmoid as opposed to a tanh will only make a marginal difference. What is more important is that the activation has a nice derivative.
An Activation Function decides whether a neuron should be activated or not. This means that it will decide whether the neuron's input to the network is important or not in the process of prediction using simpler mathematical operations.
No, they are the same. I also quote from wikipedia: "Usually 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. Don't take the matlab documentation too literally, it's thousand of pages long so some words might not be used in their strict sense.
In machine learning at least, they are used interchangeably by all books I've read.
So, to sum up
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