Memristive Artificial Synapses for Neuromorphic Computing

HighlightsSynaptic devices that mimic synaptic functions are discussed by categorizing them into electrically stimulated, optically stimulated, and photoelectric synergetic synaptic devices based on stimulation of electrical and optical signals.The working mechanisms, progress, and application scenarios of synaptic devices based on electrical and optical signals are compared and analyzed.The performances and future development of various synaptic devices that could be significant for building efficient neuromorphic systems are prospected. AbstractNeuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the von Neumann architecture. This computing is realized based on memristive hardware neural networks in which synaptic devices that mimic biological synapses of the brain are the primary units. Mimicking synaptic functions with these devices is critical in neuromorphic systems. In the last decade, electrical and optical signals have been incorporated into the synaptic devices and promoted the simulation of various synaptic functions. In this review, these devices are discussed by categorizing them into electrically stimulated, optically stimulated, and photoelectric synergetic synaptic devices based on stimulation of electrical and optical signals. The working mechanisms of the devices are analyzed in detail. This is followed by a discussion of the progress in mimicking synaptic functions. In addition, existing application scenarios of various synaptic devices are outlined. Furthermore, the performances and future development of the synaptic devices that could be significant for building efficient neuromorphic systems are prospected.

Automated summary

This review discusses synaptic devices that mimic synaptic functions based on electrical and optical signals, categorizing them into electrically stimulated, optically stimulated, and photoelectric synergetic synaptic devices. The working mechanisms, progress, and application scenarios of these devices are compared and analyzed, and the performances and future development of these synaptic devices for efficient neuromorphic systems are prospected.