A memristive switching uncertainty model
A memristive switching uncertainty model
In this paper we endeavour to evaluate and model switching noise in resistive random access memory devices (RRAM). Although noise is always present in physical systems, the sources of which can be attributed to many different effects, in this study we are focusing our attention on a specific type -- switching noise. Using alternating pulse programming and read trains across different voltages we acquire a large dataset below and above the switching threshold and construct what we define as increment plots, ΔR vs. R. Then, through a detailed statistical analysis, we quantify the localised uncertainty among consecutive points using a sliding window of up to N points accounting for any statistical artefacts that arise. By separating the data accumulated from programming and read-out and analysing them individually we can subtract a baseline noise floor from the overall switching uncertainty. In this way we effectively decouple it from other noise sources that affect the device at rest. In the end an F(R,V) surface can be extracted that closely follows the behaviour of uncertainty of the device during programming. This modelled surface can be used as an approximation of the noise behaviour of the device or it can be readily incorporated as an additional component to existing switching models.
2946-2953
Stathopoulos, Spyros
98d12f06-ad01-4708-be19-a97282968ee6
Serb, Alexantrou
30f5ec26-f51d-42b3-85fd-0325a27a792c
Khiat, Ali
bf549ddd-5356-4a7d-9c12-eb6c0d904050
Ogorzałek, Maciej
440112e9-3d28-4a9f-afd7-26a4f60f3ca7
Prodromakis, Themis
d58c9c10-9d25-4d22-b155-06c8437acfbf
July 2019
Stathopoulos, Spyros
98d12f06-ad01-4708-be19-a97282968ee6
Serb, Alexantrou
30f5ec26-f51d-42b3-85fd-0325a27a792c
Khiat, Ali
bf549ddd-5356-4a7d-9c12-eb6c0d904050
Ogorzałek, Maciej
440112e9-3d28-4a9f-afd7-26a4f60f3ca7
Prodromakis, Themis
d58c9c10-9d25-4d22-b155-06c8437acfbf
Stathopoulos, Spyros, Serb, Alexantrou, Khiat, Ali, Ogorzałek, Maciej and Prodromakis, Themis
(2019)
A memristive switching uncertainty model.
IEEE Transactions on Electron Devices, 66 (7), .
(doi:10.1109/TED.2019.2918102).
Abstract
In this paper we endeavour to evaluate and model switching noise in resistive random access memory devices (RRAM). Although noise is always present in physical systems, the sources of which can be attributed to many different effects, in this study we are focusing our attention on a specific type -- switching noise. Using alternating pulse programming and read trains across different voltages we acquire a large dataset below and above the switching threshold and construct what we define as increment plots, ΔR vs. R. Then, through a detailed statistical analysis, we quantify the localised uncertainty among consecutive points using a sliding window of up to N points accounting for any statistical artefacts that arise. By separating the data accumulated from programming and read-out and analysing them individually we can subtract a baseline noise floor from the overall switching uncertainty. In this way we effectively decouple it from other noise sources that affect the device at rest. In the end an F(R,V) surface can be extracted that closely follows the behaviour of uncertainty of the device during programming. This modelled surface can be used as an approximation of the noise behaviour of the device or it can be readily incorporated as an additional component to existing switching models.
Text
ted-noise-final
- Accepted Manuscript
More information
Accepted/In Press date: 17 May 2019
e-pub ahead of print date: 6 June 2019
Published date: July 2019
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Local EPrints ID: 431514
URI: http://eprints.soton.ac.uk/id/eprint/431514
PURE UUID: f217ade1-6b7c-4fb8-b1c5-d6b8593609de
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Date deposited: 06 Jun 2019 16:30
Last modified: 16 Mar 2024 01:55
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Author:
Spyros Stathopoulos
Author:
Alexantrou Serb
Author:
Ali Khiat
Author:
Maciej Ogorzałek
Author:
Themis Prodromakis
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