Machine-learning by rogue waves, dispersive shocks, and solitons We study artificial neural networks with nonlinear waves as a computing reservoir. We discuss universality and the conditions to learn a dataset in terms of output channels and nonlinearity. A feed-forward three-layer model, with an encoding input layer, a wave layer, and a decoding readout, behaves as … Continue reading Theory of neuromorphic computing by waves