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Neuromorphic photonics combines the advantages of photonics with the computational power of neural networks to create novel reconfigurable processing devices. Doing so enables new applications which are difficult or impossible for conventional digital electronic or RF processors to handle. This talk will highlight recent progress in neuromorphic photonic integrated circuits (PICs), beginning with photonic neurons which integrate both the linear and nonlinear functionality. It will then cover recent demonstrations utilizing PICs, including model predictive control (MPC), RF blind source separation (BSS), nonlinearity compensation in long-haul communications, and RF fingerprinting.
Paul R. Prucnal (Fri,) studied this question.