2016
DOI: 10.1109/tnano.2015.2493960
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Stochasticity Modeling in Memristors

Abstract: Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear … Show more

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Cited by 92 publications
(60 citation statements)
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“…Current RS devices show a great degree of variability, both between different devices and different cycles [174][175][176][177] . The fundamental reason is their small size, in the nanometer scale, comparable to important structural lengths such as the grain size or the domain length in Mott insulators.…”
Section: Viii1 Immediate Challengesmentioning
confidence: 99%
“…Current RS devices show a great degree of variability, both between different devices and different cycles [174][175][176][177] . The fundamental reason is their small size, in the nanometer scale, comparable to important structural lengths such as the grain size or the domain length in Mott insulators.…”
Section: Viii1 Immediate Challengesmentioning
confidence: 99%
“…Values of the parameters of the model were set as: {a, b, c, m, f 0 , L 0 } = {15000, 0, 0.1, 82, 310}, with R OFF = 200KΩ, and R ON = 2KΩ. Variation of switching thresholds (i.e., V SET,RESET ± v o ) should ideally be minimized as much as possible to ensure high reliability [34], [35]. In the simulations, the threshold values V SET = |V RESET | = 0.3V were used as mean values of normal distributions with a small standard deviation, which we then used to decide on the proper programming pulse amplitudes.…”
Section: Spice Simulation Resultsmentioning
confidence: 99%
“…Even though most of the memristor models used for simulations illustrate the ideal switching behavior, the real devices show the variability in switching behavior. Several works investigate the probability of switching of the memristive devices and apply this property in the stochastic systems [145]. While the stochasticity in switching may be useful for some systems, the effects of this behavior on various neuromorphic architectures and learning systems have not been investigated yet.…”
Section: B Major Issues Open Problems and Future Work Prospectivementioning
confidence: 99%