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A Dynamical Compact Model of Diffusive and Drift Memristors for Neuromorphic Computing

Ye Zhuo, Rivu Midya, Wenhao Song, Zhongrui Wang, Shiva Asapu, Mingyi Rao, Peng Lin, Hao Jiang, Qiangfei Xia, R. Stanley Williams, J. Joshua Yang

2021Advanced Electronic Materials41 citationsDOI

Abstract

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.

Topics & Concepts

MemristorNeuromorphic engineeringMemistorSet (abstract data type)Resistive random-access memoryStatistical physicsComputer scienceConductanceWork (physics)Materials scienceElectronic engineeringArtificial neural networkPhysicsArtificial intelligenceVoltageEngineeringQuantum mechanicsCondensed matter physicsProgramming languageAdvanced Memory and Neural ComputingNeural dynamics and brain functionPhotoreceptor and optogenetics research