Optical signal processing with a network of semiconductor optical amplifiers in the context of photonic reservoir computing
Kristof Vandoorne, Martin Fiers, David Verstraeten, Benjamin Schrauwen, Joni Dambre, Peter Bienstman · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Photonic reservoir computing is a hardware implementation of the concept of reservoir computing which comes from the field of machine learning and artificial neural networks. This concept is very useful for solving all kinds of classification and recognition problems. Examples are time series prediction, speech and image recognition. Reservoir computing often competes with the state-of-the-art. Dedicated photonic hardware would offer advantages in speed and power consumption. We show that a network of coupled semiconductor optical amplifiers can be used as a reservoir by using it on a benchmark isolated words recognition task. The results are comparable to existing software implementations and fabrication tolerances can actually improve the robustness.