Name
Title | ||
|---|---|---|
CDF Distance Based Statistical Parameter Extraction Using Nonlinear Delay Variation Models |
Abstract | ||
|---|---|---|
This paper proposes a parameter extraction method by comparing the cumulative distribution functions (CDF) between measurement and model-based estimation. We propose a nonlinear delay variation model for fast Monte Carlo simulation to obtain CDFs. We demonstrate the validity of our method by extracting within-die and random telegraph noise induced threshold voltage variations using measured data obtained from a 65 nm test structure. Our proposed method can accurately extract the statistical parameters and can reproduce the measured delay variations by simulation. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IOLTS52814.2021.9486684 | 2021 IEEE 27th International Symposium on On-Line Testing and Robust System Design (IOLTS) |
Keywords | DocType | ISSN |
delay variations,statistical parameters,random telegraph noise induced threshold voltage variations,fast Monte Carlo simulation,model-based estimation,cumulative distribution functions,nonlinear delay variation model,statistical parameter extraction,CDF distance,size 65.0 nm | Conference | 1942-9398 |
ISBN | Citations | PageRank |
978-1-6654-3371-6 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kensuke Murakami | 1 | 0 | 0.34 |
| Mahfuzul Islam | 2 | 1 | 0.73 |
| Hidetoshi Onodera | 3 | 455 | 105.29 |