Probabilistic Computing With Neuromorphic Elements https://sscs.ieee.org/wp-content/themes/movedo/images/empty/thumbnail.jpg 150 150 https://secure.gravatar.com/avatar/8fcdccb598784519a6037b6f80b02dee03caa773fc8d223c13bfce179d70f915?s=96&d=mm&r=g
Abstract:
This article presents a compact and low-power approach to probabilistic inference based on time-domain analog computation. The proposed system implements a Bayesian classifier using neuromorphic circuit elements simulated in a 130-nm CMOS technology. Probabilities are encoded in the duty cycle of deterministic spiking signals generated by neuron circuits, while likelihood …