memristive device modeling

Constructing physics-informed device and circuit models of memristors and their array-level interactions, including variability and reliability effects, to enable mapping of logic primitives (e.g., IMPLY) and algorithms onto memristive crossbars while satisfying device, circuit, and reliability constraints.

memristivedevicemodeling

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Hot Scholars

EC

Erika Covi

Zernike Institute for Advanced Materials & CogniGron Center, University of Groningen
Memristive devicesNeuromorphic computingSpiking Neural NetworksElectronic engineering
LF

Luca Fehlings

University of Groningen
memory deviceselectron devicesDTCO
GI

Giacomo Indiveri

Institute of Neuroinformatics, University of Zurich and ETH Zurich
Neuromorphic EngineeringNeuroscienceBio-signal processingLearning
YV

Yuriy V. Pershin

Professor of Physics, University of South Carolina
Condensed matter physicscomputational physicsspintronicsmemory effects