In this Letter, we theoretically investigate the application of a
bistable Fabry–Perot semiconductor laser under optical injection as an
all-optical activation unit for multilayer perceptron optical neural
networks. The proposed device is programmed to provide reconfigurable
sigmoid-like activation functions with adjustable thresholds and
saturation points and benchmarked on machine learning image
recognition problems. Due to the reconfigurability of the activation
unit, the accuracy can be increased by up to 2% simply by adjusting
the control parameter of the activation unit to suit the specific
problem. For a simple two-layer perceptron neural network, we achieve
inference accuracies of up to 95% and 85%, for the MNIST and
Fashion-MNIST datasets, respectively.