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Short Communication: An Updated Design to Implement Artificial Neuron Synaptic Behaviors in One Device with a Control Gate.
International Journal of Nanomedicine ( IF 6.6 ) Pub Date : 2020-08-20 , DOI: 10.2147/ijn.s223651
Shaocheng Qi 1 , Yongbin Hu 1 , Chaoqi Dai 1 , Peiqin Chen 1 , Zhendong Wu 1 , Thomas J Webster 2 , Mingzhi Dai 1, 3
Affiliation  

Background: As a key component in artificial intelligence computing, a transistor design is updated here as a potential alternative candidate for artificial synaptic behavior implementation. However, further updates are needed to better control artificial synaptic behavior. Here, an updated channel-electrode transistor design is proposed as an artificial synapse device; this structure is different from previously published designs by other groups.
Methods: A semiconductor characterization system was used in order to simulate the artificial synaptic behavior and a scanning electron microscope was used to characterize the device structure.
Results: It was found that the electrode added to the transistor channel had a strong impact on the representative transmission behavior of such artificial synaptic devices, such as excitatory postsynaptic current (EPSC) and the paired-pulse facilitation (PPF) index.
Conclusion: These behaviors were tuned effectively and the impact of the channel electrode is explained by the combined effects of the joint channel electrode and conventional gate. The voltage dependence of such oxide devices suggests more capability to emulate various synaptic behaviors for numerous medical and non-medical applications. This is extremely helpful for future neuromorphic computational system implementation.



中文翻译:

短通信:在一个带有控制门的设备中实现人工神经元突触行为的更新设计。

背景:作为人工智能计算的关键组件,晶体管设计在这里被更新为人工突触行为实现的潜在替代候选者。然而,需要进一步更新以更好地控制人工突触行为。在这里,提出了一种更新的通道电极晶体管设计作为人工突触装置。这种结构不同于其他团体之前发布的设计。
方法:使用半导体表征系统来模拟人工突触行为,并使用扫描电子显微镜表征器件结构。
结果:发现添加到晶体管通道的电极对这种人工突触装置的代表性传输行为有很大影响,例如兴奋性突触后电流 (EPSC) 和配对脉冲促进 (PPF) 指数。
结论:这些行为得到了有效的调整,通道电极的影响可以通过联合通道电极和常规栅极的组合效应来解释。这种氧化物器件的电压依赖性表明,在众多医疗和非医疗应用中模拟各种突触行为的能力更强。这对于未来的神经形态计算系统实现非常有帮助。

更新日期:2020-08-20
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