神经形态工程学
记忆电阻器
材料科学
光电子学
计算机科学
人工神经网络
突触重量
光学计算
逻辑门
电子工程
人工智能
计算机体系结构
工程类
算法
作者
Junlin Fang,Zhenhua Tang,Xi-Cai Lai,Fan Qiu,Yanping Jiang,Qiu‐Xiang Liu,Xin‐Gui Tang,Qijun Sun,Yichun Zhou,Jingmin Fan,Ju Gao
标识
DOI:10.1021/acsami.4c05316
摘要
Today's computing systems, to meet the enormous demands of information processing, have driven the development of brain-inspired neuromorphic systems. However, there are relatively few optoelectronic devices in most brain-inspired neuromorphic systems that can simultaneously regulate the conductivity through both optical and electrical signals. In this work, the Au/MXene/Y:HfO2/FTO ferroelectric memristor as an optoelectronic artificial synaptic device exhibited both digital and analog resistance switching (RS) behaviors under different voltages with a good switching ratio (>103). Under optoelectronic conditions, optimal weight update parameters and an enhanced algorithm achieved 97.1% recognition accuracy in convolutional neural networks. A new logic gate circuit specifically designed for optoelectronic inputs was established. Furthermore, the device integrates the impact of relative humidity to develop an innovative three-person voting mechanism with a veto power. These results provide a feasible approach for integrating optoelectronic artificial synapses with logic-based computing devices.
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