{"title":"Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network","authors":"Jingon Jang, Yoonseok Song, Sungjun Park","doi":"10.1002/aisy.202570012","DOIUrl":null,"url":null,"abstract":"<p><b>Analog Memristor Characteristics</b>\n </p><p>The systematic design of memristor-based neural network is provided by analog conductance state parameters to accurately emulate the software-based high-resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of 5% for inference accuracy of ≈84.36% and loss value of ≈0.168. Further details can be found in article number 2400710 by Jingon Jang, Yoonseok Song, and Sungjun Park.\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"7 3","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202570012","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","FirstCategoryId":"1085","ListUrlMain":"https://advanced.onlinelibrary.wiley.com/doi/10.1002/aisy.202570012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Analog Memristor Characteristics
The systematic design of memristor-based neural network is provided by analog conductance state parameters to accurately emulate the software-based high-resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of 5% for inference accuracy of ≈84.36% and loss value of ≈0.168. Further details can be found in article number 2400710 by Jingon Jang, Yoonseok Song, and Sungjun Park.
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