神经形态工程学
终端(电信)
计算机科学
可扩展性
Spike(软件开发)
人工神经网络
尖峰神经网络
人工智能
计算机网络
软件工程
数据库
作者
Guoqing Li,Mingzhi Dai,Yuejun Zhang
标识
DOI:10.1002/aelm.202101003
摘要
Abstract Artificial synaptic devices have attracted attention because such devices with brain‐like spike‐based characteristics are the basis for developing neuromorphic computing and artificial intelligence. Electric devices for artificial synaptic devices typically include two‐terminal and three‐terminal devices. However, there is a gap between the massive multi‐terminal (i.e., close to 3D) 3D connectivity in the brain with stochastic inherence and devices under 2D control, owing to the limited number of terminals, that is, two or three number of terminalsterminals. There is a need for updated designs that can bridge the gap between electronic devices that cannot mimic artificial synaptic behaviors effectively and large‐scale circuits that can mimic those multi‐terminal behaviors effectively but consume considerable amounts of power. Herein, multi‐terminal brain‐like artificial synaptic devices with small footprint and spike‐based behaviors, the structure of which is developed frombased on a standard transistor, which and could have a good potential of mass application due towith the structure's nice area efficiency and scalability, are proposed. These devices have an increased ability to mimic stochastic inherence behaviors but require lower energy than existing complex computing platforms. This design effectively mimics the artificial synaptic behaviors employed in 3D muti‐terminal connectivity control. Furthermore, it enables easier device control and fabrication in mass production. Thus, the proposed multi‐terminal devices with artificial synaptic behaviors are nice candidates for next‐generation neuromorphic computing and artificial intelligence electronic systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI