Phase-type distributions for studying variability in resistive memories

作者：

Highlights：

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• Reliability analysis of switching parameters in Resistive Random Access Memories (RRAMS) is developed.

• The lack of fit of the Weibull model is shown with data of voltage up to the conductive filament failure (Vreset).

• A new statistical modeling of Vreset based on phase-type distributions (PHDs) is introduced.

• Estimation and selection of parameters of the PHD via EM algorithm provide the Erlang distribution (ED) as the best fit.

• The ED has two parameters with a clear physical interpretation.

摘要

•Reliability analysis of switching parameters in Resistive Random Access Memories (RRAMS) is developed.•The lack of fit of the Weibull model is shown with data of voltage up to the conductive filament failure (Vreset).•A new statistical modeling of Vreset based on phase-type distributions (PHDs) is introduced.•Estimation and selection of parameters of the PHD via EM algorithm provide the Erlang distribution (ED) as the best fit.•The ED has two parameters with a clear physical interpretation.

论文关键词：Resistive switching memory,Conductive filaments,Reset process,Weibull distribution,Phase-type distributions,Statistical modeling

论文评审过程：Received 16 March 2018, Revised 5 June 2018, Available online 18 June 2018, Version of Record 28 June 2018.

论文官网地址：https://doi.org/10.1016/j.cam.2018.06.010