DEVICE AND METHOD FOR TRAINING A CLASSIFIER

Computer-implemented method for training a classifier (60) for classifying input signals (x) provided to the classifier (60), wherein the classifier (60) is configured to obtain an output signal (y) characterizing a classification of the input signal (x), wherein the method for training comprises the following steps:a. Providing (601) a set of perturbations;b. Providing (602) a subset of first training samples each comprising an input signal and a corresponding desired output signal from a first dataset of training samples;c. Selecting (603) a first perturbation form the set of perturbations for an input signal and a corresponding desired output signal from the subset;d. Obtaining (604) a second perturbation, which is stronger than the first perturbation, by adapting the first perturbation based on the input signal, the corresponding desired output signal and the classifier;e. Obtaining (605) a first adversarial example by applying the second perturbation to the input signal;f. Adapting (606) the classifier (60) by training the classifier (60) based on the first adversarial example and the corresponding desired output signal to harden the classifier (60) against the second perturbation;g. Replacing (607) the first perturbation in the set of perturbations a linear combination of the first perturbation and the second perturbation;