记忆电阻器
神经形态工程学
记忆晶体管
集合(抽象数据类型)
电阻随机存取存储器
统计物理学
电导
工作(物理)
计算机科学
材料科学
电子工程
人工神经网络
拓扑(电路)
物理
人工智能
电气工程
电压
工程类
量子力学
凝聚态物理
程序设计语言
作者
Ye Zhuo,Rivu Midya,Wenhao Song,Zhongrui Wang,Shiva Asapu,Mingyi Rao,Peng Lin,Hao Jiang,Qiangfei Xia,R. Stanley Williams,J. Joshua Yang
标识
DOI:10.1002/aelm.202100696
摘要
Abstract Different from nonvolatile memory applications, neuromorphic computing applications utilize not only the static conductance states but also the switching dynamics for computing, which calls for compact dynamical models of memristive devices. In this work, a generalized model to simulate diffusive and drift memristors with the same set of equations is presented, which have been used to reproduce experimental results faithfully. The diffusive memristor is chosen as the basis for the generalized model because it possesses complex dynamical properties that are difficult to model efficiently. A data set from statistical measurements on SiO 2 :Ag diffusive memristors is collected to verify the validity of the general model. As an application example, spike‐timing‐dependent plasticity is demonstrated with an artificial synapse consisting of a diffusive memristor and a drift memristor, both modeled with this comprehensive compact model.
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