Abstract: A method for training a neural network, which includes a first number of layers. In the method, in a training sequence, which includes a plurality of training patterns, using a backpropagation algorithm, when applying the backpropagation algorithm during each of the plurality of training patterns, in each case a second number of layers of the neural network being disregarded, an absolute value of the second number being variable and being randomly selected before each of the number of training patterns under the condition that the absolute value is greater than or equal to zero and simultaneously smaller than an absolute value of the first number, and the second number of layers being an input layer of the neural network and layers of the neural network immediately following the input layer.