Simulated Resistive Drift of Memristive Devices

Citation Author(s):
Waleed
El-Geresy
Imperial College London
Submitted by:
Waleed El-Geresy
Last updated:
Fri, 12/13/2024 - 19:37
DOI:
10.21227/edzz-7d60
Data Format:
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License:
Creative Commons Attribution
4 Views
Categories:
Artificial Intelligence
Machine Learning
Keywords:
memristors, resistive drift, memristive devices
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Abstract 

A dataset of simulated resistive drift series for an illustrative stochastic memristor.

Dataset Description

The memristor has an equilibrium resistance of approximately 500kΩ.

5000 series are generated with starting resistances sampled uniformly from the range [100Ω, 750kΩ].

Each series consists of 1001 datapoints, with the first (zeroth) point corresponding to the initial resistance, and subsequent points sampled at subsequent timesteps.

Dataset Creation

The simulations were conducted using the event-based memristor model in [1], with parameters as follows, as specified in [2]:

N = 1.8 × 10^6

n_thresh = 0

g_parallel = 1 × 10^-6

g_step = 1 × 10^-8

V_a = 0.256

V_off = 0.2533

References

[1] Waleed El-Geresy, Christos Papavassiliou, Deniz Gündüz (2024), Event-Based Simulation of Stochastic Memristive Devices for Neuromorphic Computing, arXiv:2407.04718 [cs.ET]

[2] Waleed El-Geresy, Christos Papavassiliou, Deniz Gündüz (2024), Delay Conditioned Generative Modelling of Resistive Drift in Memristors, arXiv:2408.01539 [cs.ET]

Instructions: 

Usage

The dataset is supplied as a numpy array of dimension (5000, 1001), and can be loaded using np.load(...).

Dataset Files

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