量子点
记忆电阻器
油藏计算
任务(项目管理)
计算机科学
光电子学
材料科学
纳米技术
物理
人工智能
工程类
量子力学
人工神经网络
系统工程
循环神经网络
作者
Jiasong Lin,Zhen Wang,Qinghong Lin,Jiayu Sun,Xuan Guo,Yue Wang,Liangxu Lin,Yi Zhao,Yang Liu,Deli Li,Fushan Li
标识
DOI:10.1021/acs.jpclett.4c03350
摘要
The rise of big data and the internet of things has driven the demand for multimodal sensing and high-efficiency low-latency processing. Inspired by the human sensory system, we present a multifunctional optoelectronic-memristor-based reservoir computing (OM-RC) system by utilizing a CuSCN/PbS quantum dots (QDs) heterojunction. The OM-RC system exhibits volatile and nonlinear responses to electrical signals and wide-spectrum optical stimuli covering ultraviolet, visible, and near-infrared (NIR) regions, enabling multitask processing of dynamic signals. The OM-RC system accurately performs health monitoring through dynamic electroencephalogram and electrocardiogram signal analysis and achieves object and traffic trajectory recognition for intelligent driving under challenging conditions like foggy environments. By collaboratively using the NIR perception and trajectory recognition, we develop a human–computer interaction authentication system that integrates finger veins and motion behaviors of humans, significantly enhancing the security of traditional fingerprint anticounterfeiting systems. This work demonstrates the potential of QD-based optoelectronic-memristor for multitask in-sensor processing applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI