神经形态工程学
光电子学
材料科学
晶体管
光子学
电气工程
计算机科学
电压
工程类
人工智能
人工神经网络
作者
Yi Yang,Yongli He,Sha Nie,Yi Shi,Qing Wan
出处
期刊:IEEE Electron Device Letters
[Institute of Electrical and Electronics Engineers]
日期:2018-06-01
卷期号:39 (6): 897-900
被引量:92
标识
DOI:10.1109/led.2018.2824339
摘要
Inspired by the neocortex of the human brain, neuromorphic systems are favorable for processing a variety of complex tasks, such as recognition, prediction, and optimization. To build such an intelligent system, neuromorphic devices are in high demand. Here, photoelectric neuromorphic devices based on pulse light-stimulated low-voltage indium-gallium-zinc-oxide electric-double-layer transistors were investigated. Such devices can mimic some important synaptic behaviors, such as excitatory post-synaptic potentials, paired-pulse facilitation, and long-term plasticity in the form of photonic excitatory post-synaptic potentials. At last, depression mode to potentiation mode transition was also demonstrated by gate voltage modulation. Our photoelectric neuromorphic devices are interesting for photonic neuromorphic systems.
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