Is a neural network able to learn to map a completely different feature vector to the same class
Yes, neural networks excel at finding highly non-linear decision boundaries. For example, take a look at this demo (don't forget to click the play button to make the network learn). Even this very simple network is able to learn that the opposite corners of the input space belong to the same class.