神经形态工程学
长时程增强
纳米线
材料科学
CMOS芯片
晶体管
MNIST数据库
光电子学
计算机科学
纳米技术
电子工程
电气工程
人工神经网络
电压
人工智能
工程类
化学
生物化学
受体
作者
Md. Hasan Raza Ansari,Kannan Udaya Mohanan,Seongjae Cho
出处
期刊:Nanomaterials
[Multidisciplinary Digital Publishing Institute]
日期:2021-07-07
卷期号:11 (7): 1773-1773
被引量:21
摘要
This work showcases the physical insights of a core-shell dual-gate (CSDG) nanowire transistor as an artificial synaptic device with short/long-term potentiation and long-term depression (LTD) operation. Short-term potentiation (STP) is a temporary potentiation of a neural network, and it can be transformed into long-term potentiation (LTP) through repetitive stimulus. In this work, floating body effects and charge trapping are utilized to show the transition from STP to LTP while de-trapping the holes from the nitride layer shows the LTD operation. Furthermore, linearity and symmetry in conductance are achieved through optimal device design and biases. In a system-level simulation, with CSDG nanowire transistor a recognition accuracy of up to 92.28% is obtained in the Modified National Institute of Standards and Technology (MNIST) pattern recognition task. Complementary metal-oxide-semiconductor (CMOS) compatibility and high recognition accuracy makes the CSDG nanowire transistor a promising candidate for the implementation of neuromorphic hardware.
科研通智能强力驱动
Strongly Powered by AbleSci AI