Function activation or what we call transfer function.
Let's take a look at this one.
This is a simple neuron that we have here.
There are some inputs and here we are sending them to an activation function.
Let's talk about this activation function little bit more.
I just got all these pictures from Matlab website.
There are very good information and details and examples.
So if you got time, just go there and check them out.
Let's check it here.
No one can use any differentiable transfer function to generate output multilayer often use log siegmund
log sigmoid is a transfer function which generates output between zero and one as the neural net inputs
goes from negative infinity to positive infinity.
A famous function that we can define here.
E F of X equals two one over one plus E to the negative X.
This is a very famous function that we can use when designing our activation function.
Next one that we have here is a ten sigmoid transfer function, which we show it do in Matlab with 10
sike and then this is a sign and symbol for it.
So it just give us the output from negative one to positive one one.
The inputs are going from negative infinity to positive infinity.
This is just a tangent hyperbolic.
If you remember the function for it.
It's let me just write it here.
I'm going to just write it there.
Tensioned hyperbole to show it with 10 H.
Tenjin Hyperboles of X is equal to erase race to the X minus E to negative X over A minus the X plus
a series of the negative X.
But this is a very famous function that we can also use for our activation function.
Sigmoid output neurons are often used for pattern recognition problems line here.
We have linear output neurons that are often used for feting problems.
And that's why the output layer, which we have a fitting problem, we use these purely or let's say
linear transfer function.
This is a matlab code for purely linear transfer function.
We can just use this code.
We often use these two in a multilayer Perceptron for our hidden layer, which we have the pattern recognition
problem and we use this transfer function for our output layer.
So let's check it out and see an example on Matlab.