Time series statistical analyses (TSSA) have been employed to evaluate the variability of resistive switching memories and to model the set and reset voltages for modeling purposes. The conventional procedures behind time series theory have been used to obtain autocorrelation and partial autocorrelation functions and determine the simplest analytical models to forecast the set and reset voltages in a long series of resistive switching processes. To do so, and for the sake of generality in our study, a wide range of devices have been fabricated and measured. Different oxides and electrodes have been employed, including bilayer dielectrics in devices such as Ni/HfO2/Si-n+, Cu/HfO2/Si-n+, and Au/Ti/TiO2/SiOx/Si-n+. The TSSA models obtained allowed one to forecast the reset and set voltages in a series if previous values were known. The study of autocorrelation data between different cycles in the series allows estimating the inertia between cycles in long resistive switching series. Overall, TSSA seems to be a very promising method to evaluate the intrinsic variability of resistive switching memories.
Skip Nav Destination
Article navigation
7 May 2019
Research Article|
May 03 2019
Time series statistical analysis: A powerful tool to evaluate the variability of resistive switching memories
J. B. Roldán
;
J. B. Roldán
a)
1
Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias
, Avd. Fuentenueva s/n, 18071 Granada, Spain
a)Author to whom correspondence should be addressed: jroldan@ugr.es
Search for other works by this author on:
F. J. Alonso
;
F. J. Alonso
2
Departamento de Estadística e Investigación Operativa, Universidad de Granada, Facultad de Ciencias
, Avd. Fuentenueva s/n, 18071 Granada, Spain
Search for other works by this author on:
A. M. Aguilera
;
A. M. Aguilera
2
Departamento de Estadística e Investigación Operativa, Universidad de Granada, Facultad de Ciencias
, Avd. Fuentenueva s/n, 18071 Granada, Spain
Search for other works by this author on:
D. Maldonado;
D. Maldonado
1
Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias
, Avd. Fuentenueva s/n, 18071 Granada, Spain
Search for other works by this author on:
M. Lanza
M. Lanza
3
Institute of Functional Nano and Soft Materials (FUNSOM), Collaborative Innovation Center of Suzhou Nanoscience & Technology, Soochow University
, 199 Ren-Ai Road, Suzhou 215123, China
Search for other works by this author on:
a)Author to whom correspondence should be addressed: jroldan@ugr.es
J. Appl. Phys. 125, 174504 (2019)
Article history
Received:
October 30 2018
Accepted:
April 16 2019
Citation
J. B. Roldán, F. J. Alonso, A. M. Aguilera, D. Maldonado, M. Lanza; Time series statistical analysis: A powerful tool to evaluate the variability of resistive switching memories. J. Appl. Phys. 7 May 2019; 125 (17): 174504. https://doi.org/10.1063/1.5079409
Download citation file:
Sign in
Don't already have an account? Register
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Sign in via your Institution
Sign in via your InstitutionPay-Per-View Access
$40.00