1. A neural network for classifying sampled signals into a plurality of classes comprising: a representation transformer that accepts samples of a selected signal as input, applies a transformation to the input signal to transform the input signal into a representational space, and outputs a transformed signal, wherein the transformation distributes sampled signals belonging to a given class within the representational space in accordance with a predetermined distribution associated with the given class; and a Bayes classifier that accepts the transformed signal as an input and assigns the input signal to a class with the highest posterior probability.