Combines a feedforward neural network, parameters for which are 'learned' using an eliminational genetic algorithm. Utilizes two types of neurons: Type one (first hidden layer) - generates a similarity measurement between input data and stored parameters vectors Type two (second hidden layer - last layer) - sigmoid function. Built for an uni course.