@inproceedings{bc1688985d6041bcba68c630550324a2,
title = "A new device characteristic model generation by machine learning",
abstract = "This paper proposes a method to generate a characteristic model of a new device by machine learning. It is difficult new emerging devices and materials to have exact physical model to fit the behavior because developing physical models is complex and takes a long time. Therefore, we propose a regression method by machine learning as an alternative intermediate step of the physical model, and present guidelines for date preprocessing and proper architecture for efficient learning. It makes it easier and faster to solve general regression problems such as function generation.",
keywords = "Machine learning, model generation, New device modeling",
author = "Oh, {Min Hye} and Suhyun Bang and Kwon, {Min Woo} and Park, {Byung Gook}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Electron Devices Technology and Manufacturing Conference, EDTM 2019 ; Conference date: 12-03-2019 Through 15-03-2019",
year = "2019",
month = mar,
doi = "10.1109/EDTM.2019.8731336",
language = "English",
series = "2019 Electron Devices Technology and Manufacturing Conference, EDTM 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "466--468",
booktitle = "2019 Electron Devices Technology and Manufacturing Conference, EDTM 2019",
}