Quantitative Measure of Hysteresis for Memristors Through Explicit Dynamics
Panayiotis S. Georgiou (1, 2), Sophia N. Yaliraki (1), Emmanuel M., Drakakis (2), Mauricio Barahona (3) ((1) Department of Chemistry Imperial, College London, (2) Department of Bioengineering Imperial College London, (3), Department of Mathematics Imperial College London)

TL;DR
This paper develops a mathematical framework using Bernoulli differential equations to analytically analyze memristor dynamics, enabling explicit solutions for hysteresis quantification and device behavior without numerical simulations.
Contribution
It introduces a novel Bernoulli differential equation approach to derive explicit analytical solutions for memristor I-V characteristics and hysteresis measurement.
Findings
Analytical solutions for HP memristor I-V characteristics under various drives.
Identification of a dimensionless parameter governing hysteresis.
Explicit formulas for hysteresis quantification.
Abstract
We introduce a mathematical framework for the analysis of the input-output dynamics of externally driven memristors. We show that, under general assumptions, their dynamics comply with a Bernoulli differential equation and hence can be nonlinearly transformed into a formally solvable linear equation. The Bernoulli formalism, which applies to both charge- and flux-controlled memristors when either current- or voltage-driven, can, in some cases, lead to expressions of the output of the device as an explicit function of the input. We apply our framework to obtain analytical solutions of the i-v characteristics of the recently proposed model of the Hewlett-Packard memristor under three different drives without the need for numerical simulations. Our explicit solutions allow us to identify a dimensionless lumped parameter that combines device-specific parameters with properties of the input…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · stochastic dynamics and bifurcation · Neural dynamics and brain function
