神经形态工程学
仿真
计算机科学
人工神经元
人工神经网络
光学(聚焦)
计算神经科学
神经科学
人工智能
纳米技术
材料科学
生物
物理
经济增长
光学
经济
作者
Hefei Liu,Yuan Qin,Hung‐Yu Chen,Jiangbin Wu,Jiahui Ma,Zhonghao Du,Nan Wang,Jingyi Zou,Sen Lin,Xu Zhang,Yuhao Zhang,Han Wang
标识
DOI:10.1002/adma.202205047
摘要
Abstract Artificial neuronal devices are critical building blocks of neuromorphic computing systems and currently the subject of intense research motivated by application needs from new computing technology and more realistic brain emulation. Researchers have proposed a range of device concepts that can mimic neuronal dynamics and functions. Although the switching physics and device structures of these artificial neurons are largely different, their behaviors can be described by several neuron models in a more unified manner. In this paper, the reports of artificial neuronal devices based on emerging volatile switching materials are reviewed from the perspective of the demonstrated neuron models, with a focus on the neuronal functions implemented in these devices and the exploitation of these functions for computational and sensing applications. Furthermore, the neuroscience inspirations and engineering methods to enrich the neuronal dynamics that remain to be implemented in artificial neuronal devices and networks toward realizing the full functionalities of biological neurons are discussed.
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