TEAM: ThrEshold Adaptive Memristor Model

By Shahar Kvatinsky, Eby G. Friedman, Avinoam Kolodny, Uri C. Weiser. IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2013

759 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

MRL — Memristor Ratioed Logic (2012, methodology): “In this paper, the TEAM model [4] is used since”
MAGIC—Memristor-Aided Logic (2014, methodology): “A memristor model, the VTEAM model [20], which extends the TEAM model with a threshold voltage, is used with a Biolek window function [8].”
Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training (2015, positive): “In [Appendix A, 39], it is explained how to modify the circuit to work with more realistic memristive devices [40, 14], instead of the classical memristor model [11], given a few conditions.”
Logic Design Within Memristive Memories Using Memristor-Aided loGIC (MAGIC) (2016, background): “For current-controlled memristors [2], [37], the cumulative current may be higher than the threshold current, resulting in increased resistance of the output memristor, even when the logical state of the memristor is unchanged.”
Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies (2014, methodology): “The TEAM model [23] is used here to estimate the circuit parameters.”