Training of artificial neural networks

Methods and apparatus are provided for training an artificial neural network, having a succession of neuron layers with interposed synaptic layers each storing a respective set of weights {w} for weighting signals propagated between its adjacent neuron layers, via an iterative cycle of signal propagation and weight-update calculation operations. Such a method includes, for at least one of the synaptic layers, providing a plurality Pl of arrays of memristive devices, each array storing the set of weights of that synaptic layer Sl in respective memristive devices, and, in a signal propagation operation, supplying respective subsets of the signals to be weighted by the synaptic layer Sl in parallel to the Pl arrays. The method also includes, in a weight-update calculation operation, calculating updates to respective weights stored in each of the Pl arrays in dependence on signals propagated by the neuron layers.