1. A method for training a neural network which includes at least one intermediate layer and for processing input data with the trained neural network, the method comprising the steps of: producing an average value of plural learning data; subtracting the average value from each of the plural learning data to obtain first difference data; fixing a bias for the at least one intermediate layer to zero; training the neural network, in which the bias for the at least one intermediate layer remains fixed to zero, with the first difference data; subtracting the average value from the input data to obtain second difference data; supplying the second difference data to the trained neural network, the neural network outputting a value as a function of the second difference data; and categorizing the input data on the basis of the value output from the neural network.