A Dynamical Compact Model of Diffusive and Drift Memristors for Neuromorphic Computing. (13th October 2021) - Zhuo, Ye; Midya, Rivu; Song, Wenhao; Wang, Zhongrui; Asapu, Shiva; Rao, Mingyi; Lin, Peng; Jiang, Hao; Xia, Qiangfei; Williams, R. Stanley; Yang, J. Joshua
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 SiO2 :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. Abstract : A dynamical model that can reproduce the long‐term memory of drift memristors and the short‐term plasticity of diffusive memristors is demonstrated. It is shown that the model captures the quasi‐static and dynamic characteristics of these devices. A decent agreement has been observed between simulation results and the experimental data.