Bit-Error Rate Performance on BPSK Label Recognition Using Complex-Valued Neural Network Trained by Noise-Added Signal

We propose an optical neural network circuit consisting of optical amplifiers, phase shifters and nonlinear threshold devices to process BPSK labels. Numerical simulation reveals that bit-error rate performance is improved by using noise-added teacher signals.