@misc{10481/69354,
year = {2019},
month = {1},
url = {http://hdl.handle.net/10481/69354},
abstract = {A new statistical approach has been developed to analyze Resistive Random Access Memory (RRAM) variability. The stochastic nature of the physical processes behind the operation of resistive memories makes variability one of the key issues to solve from the industrial viewpoint of these new devices. The statistical features of variability have been usually studied making use of Weibull distribution. However, this probability distribution does not work correctly for some resistive memories, in particular for those based on the Ni/HfO2/Si structure thar has been employed in this work. A completely new approach based on phase-type modelling is proposed in this paper to characterize the randomness of resistive memories operation. An in-depth comparision with experimental results shows that the fitted phase-type distribution works better than the Weibull distribution and also helps to understand the physics of the resistive memories.},
organization = {Spanish Ministry of Economy and Competitiveness (FEDER program) TEC2017-84321-C4-3-R MTM2017-88708-P},
organization = {IMB-CNM (CSIC) (Barcelona)},
publisher = {Elsevier},
keywords = {Resistive switching memory},
keywords = {Conductive filaments},
keywords = {Reset process},
keywords = {Weibull distribution},
keywords = {Phase-type distributions},
keywords = {Statistical modeling},
title = {Phase-type distributions for studying variability in resistve memories},
doi = {https://doi.org/10.1016/j.cam.2018.06.010},
author = {Acal González, Christian José and Ruiz-Castro, Juan Eloy and Aguilera Del Pino, Ana María and Jimenez- Molinos, Francisco and Roldán Aranda, Juan Bautista},
}