Fig. 1: Operating Principle.
Data is encoded in in the time-domain as a train of optical pulses (represented as blue dots in the equivalent neural network diagram). This pulse train is then injected into an optical fiber where distributed feedback is mediated by Rayleigh backscattering. The distributed feedback produces a series of delayed copies of the original data with random phase and amplitude (the yellow dots in the neural network diagram). Recording the backscattered signal on a photodetector then provides a non-linear transform. Overall, this process results in a random non-linear projection of the original data into a higher dimensional space, facilitating a variety of computing and data analysis tasks including non-linear principal component analysis (PCA), support vector machine (SVM), or extreme learning machine (ELM).
