Enhanced IC modeling methodology for system-level ESD simulation

Jie Xiong, Zaichen Chen, Yang Xiu, Zhen Mu, Maxim Raginsky, Elyse Rosenbaum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To enable accurate system-level ESD simulation, the quasi-static I-V model of an IC is enhanced through kernel regression to reflect its circuit board dependency; alternatively, a recurrent neural network may be used to generate a non-quasi-static transient model. Hybrid electromagnetic and circuit simulation is demonstrated for ESD-induced noise coupling analysis.

Original languageEnglish (US)
Title of host publicationElectrical Overstress/Electrostatic Discharge Symposium Proceedings, EOS/ESD 2018
PublisherESD Association
ISBN (Electronic)1585373028
StatePublished - Oct 25 2018
Event40th Annual Electrical Overstress/Electrostatic Discharge Symposium, EOS/ESD 2018 - Reno, United States
Duration: Sep 23 2018Sep 28 2018

Publication series

NameElectrical Overstress/Electrostatic Discharge Symposium Proceedings
Volume2018-September
ISSN (Print)0739-5159

Other

Other40th Annual Electrical Overstress/Electrostatic Discharge Symposium, EOS/ESD 2018
CountryUnited States
CityReno
Period9/23/189/28/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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  • Cite this

    Xiong, J., Chen, Z., Xiu, Y., Mu, Z., Raginsky, M., & Rosenbaum, E. (2018). Enhanced IC modeling methodology for system-level ESD simulation. In Electrical Overstress/Electrostatic Discharge Symposium Proceedings, EOS/ESD 2018 (Electrical Overstress/Electrostatic Discharge Symposium Proceedings; Vol. 2018-September). ESD Association.