Qirui Zhang, Weilun Ouyang, Xuemei Wang, Fan Yang, Jiangang Chen, Zhixing Wen, Jiaxin Liu, Ge Wang, Qing Liu, Fucai Liu
{"title":"Dynamic Memristors for Physical Reservoir Computing","authors":"Qirui Zhang, Weilun Ouyang, Xuemei Wang, Fan Yang, Jiangang Chen, Zhixing Wen, Jiaxin Liu, Ge Wang, Qing Liu, Fucai Liu","doi":"10.1039/d4nr01445f","DOIUrl":null,"url":null,"abstract":"Reservoir computing (RC) has garnered considerable attention for its efficient handling of temporal signal and lower training costs. As a nonlinear dynamical system, RC can map low-dimensional inputs into high-dimensional spaces and extract task-relevant features using a simple linear readout layer. Memristor inherently exhibits high-order dynamic characteristics due to their physical processes, which renders them an ideal choice for the implementation of physical reservoir computing (PRC) systems. This review focuses on PRC systems based on memristor, explaining the resistive switching mechanism at the device level and emphasizing the tunability of their dynamic behavior. The development of memristor-based reservoir computing systems is highlighted, along with discussions on the challenges faced by this field and potential future research directions.","PeriodicalId":92,"journal":{"name":"Nanoscale","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanoscale","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1039/d4nr01445f","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Reservoir computing (RC) has garnered considerable attention for its efficient handling of temporal signal and lower training costs. As a nonlinear dynamical system, RC can map low-dimensional inputs into high-dimensional spaces and extract task-relevant features using a simple linear readout layer. Memristor inherently exhibits high-order dynamic characteristics due to their physical processes, which renders them an ideal choice for the implementation of physical reservoir computing (PRC) systems. This review focuses on PRC systems based on memristor, explaining the resistive switching mechanism at the device level and emphasizing the tunability of their dynamic behavior. The development of memristor-based reservoir computing systems is highlighted, along with discussions on the challenges faced by this field and potential future research directions.
期刊介绍:
Nanoscale is a high-impact international journal, publishing high-quality research across nanoscience and nanotechnology. Nanoscale publishes a full mix of research articles on experimental and theoretical work, including reviews, communications, and full papers.Highly interdisciplinary, this journal appeals to scientists, researchers and professionals interested in nanoscience and nanotechnology, quantum materials and quantum technology, including the areas of physics, chemistry, biology, medicine, materials, energy/environment, information technology, detection science, healthcare and drug discovery, and electronics.