A feedforward neural network (FNN) is an artificial neural network wherein connections between the nodes do not form a cycle.
Most universal approximation theorems can be parsed into two classes.
- arbitrary width case
arbitrary depth case
In addition to these two classes, bounded depth and bounded width case
Universal approximation + learning algorithm.
+ so I am reading a nice book nice chapter on universal approximation theorem the proof of the universal approximation theorem here at the beginning the author mentioned that the universal approximation theorem is good and cool thing but there are other things that has this capability of universal approximation for example the Boolean circuits but what is amazing about the neural network is that it comes with two things one is the universality the universality of its ability to approximate and the learning algorithm so this learning algorithm plus the universality makes it this neural network amazing