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An integrated method for extracting the statistical distribution of RTN time constants

Mehedi, M, Tok, KH, Zhang, JF, Ji, Z, Ye, Z, Zhang, WD and Marsland, J (2021) An integrated method for extracting the statistical distribution of RTN time constants. In: IEEE Explore . (IEEE 14th International Conference on ASIC (ASICON), 26 October 2021 - 29 October 2021, Kunming, China (Online)).

Zhang-JF-Liverpool-invited-ASICON2021-v2.pdf - Accepted Version

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Modelling Random Telegraph Noise (RTN) is a challenging task and its accuracy is generally unknown. The Monte Carlo modelling in the time domain requires the statistical distribution of the capture and emission time (CET) constant of traps. Although a lot of efforts were made in early works to extract the CET of individual traps, the number of traps measured is generally too limited to establish the statistical distribution of CET reliably and there are disagreements on the statistical models of CET. Two models proposed by early works are Log-normal and Log-uniform distributions, which gives very different predictions for the RTN and this difference increases as the time window becomes wider. As an accurate modelling of RTN cannot be achieved without a trustable statistical distribution of CET, it is important to find a method that allows extracting the CET distribution reliably. In contrast with early works that focus on measuring the CET of individual traps, this work proposes an integrated method for extracting the statistical distribution of CET.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 20X21 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Engineering
Publisher: IEEE
Date Deposited: 28 Oct 2021 11:04
Last Modified: 02 Dec 2021 12:04
URI: https://researchonline.ljmu.ac.uk/id/eprint/15712

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