A New Method of Automatic Extraction of RTN and OMI-friendly implementation

被引：0
|
作者：
Xiao, Yu [1 ,2 ,3 ]
Zhang, Chenyang [1 ,2 ,3 ]
Wang, Da [1 ,2 ,3 ]
Xue, Yongkang [1 ,2 ,3 ]
Ren, Pengpeng [1 ,2 ,3 ]
Ji, Zhigang [1 ,2 ,3 ]
机构：
[1] Shanghai Jiao Tong Univ, Natl Key Lab Sci & Technol Micro Nano Fabricat, Shanghai, Peoples R China
[2] Peking Univ, Beijing, Peoples R China
[3] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Dept Micro Nano Elect, Shanghai, Peoples R China
来源：
2024 IEEE INTERNATIONAL RELIABILITY PHYSICS SYMPOSIUM, IRPS 2024 | 2024年
基金：
中国国家自然科学基金;
关键词：
Random telegraph noise; Hidden Markov model; Gaussian identification; adaptive model; open model interface; NOISE;
D O I：
10.1109/IRPS48228.2024.10529452
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, based on the non-Gaussian nature of RTN, we propose a method for the fully automated random telegraph noise (RTN) analysis, including the detection/identification of the number of traps and extraction of each trap's parameter, which makes the analysis of complex RTN more effective. By improving the efficiency of the hidden Markov model (HMM) algorithm through an adaptive model, over 10 times faster performance has been achieved compared to the conventional method. Finally, we incorporate the compact model of RTN into the circuit simulator by utilizing the Open Model Interface (OMI). This integration allows for better evaluation on the impact of RTN through circuit-level simulations, facilitating the resilient and robust future circuit designs.
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收藏
页数：4
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