A CMOS Spiking Neuron for Brain-Inspired Neural Networks With Resistive Synapses and In Situ Learning

摘要

Nanoscale resistive memory devices are expected to fuel dense integration of electronic synapses for large-scale neuromorphic systems. To realize such a brain-inspired computing chip, a compact CMOS spiking neuron that performs learning and computing while driving a large number of resistive synapses is desired. This brief presents a novel leaky integrate-and-fire neuron design that implements the dual-mode operation of current integration and synaptic drive, with a single operational amplifier (opamp) and enables learning with crossbar resistive synapses. The proposed design was implemented in a 0.18- CMOS technology. Measurements show neuron's ability to drive a thousand resistive synapses and demonstrate associative learning. The neuron circuit occupies a small area of 0.01 mm and has an energy efficiency value of 9.3 pJ/spike/synapse.