@inproceedings{76890f8e7f6f4a118976eb8a5ef1d33d,
title = "Stochastic modeling of air electrostatic discharge parameters",
abstract = "An automated tester is built for IEC 61000-4-2 air discharges. The relations between the parameters of the resulting waveforms are studied using stochastic modeling. The precharge voltage, peak current and rise time are interrelated, with a strong dependence on the humidity. However, there is no clear dependence of the peak current and rise time on the approach speed. Na{\"i}ve Bayes method is used to predict the peak current and rise time from the precharge voltage and humidity. The likelihood that a tablet experiences a soft failure is predicted via logistic regression.",
keywords = "System-level ESD, air discharge, stochastic modeling",
author = "Yang Xiu and Samuel Sagan and Advika Battini and Xiao Ma and Maxim Raginsky and Elyse Rosenbaum",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Reliability Physics Symposium, IRPS 2018 ; Conference date: 11-03-2018 Through 15-03-2018",
year = "2018",
month = may,
day = "25",
doi = "10.1109/IRPS.2018.8353548",
language = "English (US)",
series = "IEEE International Reliability Physics Symposium Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2C.21--2C.210",
booktitle = "2018 IEEE International Reliability Physics Symposium, IRPS 2018",
address = "United States",
}