Question

Let’s say you have 3 inputs: A, B, C. Can an artificial neural network (not necessarily feed forward) learn this pattern?

if C > k
   output is A
else
   output is B

Are there curtain types of networks, which can or which are well suited for this type of problem?

Answer 1

Yes, that’s a relatively easy pattern for a feedforward neural network to learn.

You will need at least 3 layers I think assuming sigmoid functions:

• 1st layer can test C>k (and possibly also scale A and B down into the linear range of the sigmoid function)
• 2nd layer can calculate A/0 and 0/B conditional on the 1st layer
• 3rd (output) layer can perform a weighted sum to give A/B (you may need to make this layer linear rather than sigmoid depending on the scale of values you want)

Having said that, if you genuinely know the structure of you problem and what kind of calculation you want to perform, then Neural Networks are unlikely to be the most effective solution: they are better in situations when you don’t know much about the exact calculations required to model the functions / relationships.