TRAINING NEURAL NETWORKS FOR EFFICIENT IMPLEMENTATION ON HARDWARE

摘要

A method (100) for training an artificial neural network, ANN (1), which comprises a plurality of neurons (2), comprising the following steps: • a measure of the quality (11) that the ANN (1) has achieved overall within a past time period is determined (110); • one or more neurons (2) are evaluated on the basis of a measure of their respective quantitative contributions (21) to the determined quality (11) (120); • actions (22), by means of which the evaluated neurons (2) are respectively trained in the further course of the training, and/or weights (23) of said neurons (2) in the ANN (1) are defined on the basis of the evaluations (120a) of the neurons (2) (130). The method (200) according to claim 11, wherein a computing unit (4) having hardware resources for a specified number of neurons (2), layers (3a, 3b) of neurons (2) and/or connections (25) between neurons (2) is selected (205a), and wherein a model (1a) of the ANN (1) having a number of neurons (2), layers (3a, 3b) of neurons (2) and/or connections (25) between neurons (2) that exceeds the specified number is selected (205b).