Fixed-Weight learning Neural Networks on Optical Hardware

Fixed-weight learning embeds a learning algorithm into the neural network topology, so its learning can take advantage of all speed increases in its operation on optical neural hardware, up to 10,000 times conventional networks. We developed a hardware-in-the-loop Optical Hardware-based Neural Network Test Apparatus. We used the apparatus to research and develop various embedded learning methods; to work out alignment, calibration, and noise reduction methods; study synaptic weight and neural signal encoding; and to test several small fixed-weight learning neural networks.