神经形态工程学
计算机科学
调制(音乐)
可塑性
突触可塑性
计算机体系结构
神经科学
人工智能
人工神经网络
材料科学
物理
生物
声学
生物化学
复合材料
受体
作者
Yilin Sun,Huaipeng Wang,Dan Xie
出处
期刊:Nano-micro Letters
[Springer Science+Business Media]
日期:2024-06-06
卷期号:16 (1)
被引量:38
标识
DOI:10.1007/s40820-024-01445-x
摘要
Abstract Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artificial intelligence. However, great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years. Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation, improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions. Herein, several fascinating strategies for synaptic plasticity modulation through chemical techniques, device structure design, and physical signal sensing are reviewed. For chemical techniques, the underlying mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted. Based on device structure design, the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions. Besides, integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light, strain, and temperature. Finally, considering that the relevant technology is still in the basic exploration stage, some prospects or development suggestions are put forward to promote the development of neuromorphic devices.
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