Fast and accurate deep neural network (DNN)-based eye-height and eye-width estimation method = 심층 신경망 기반의 빠르고 정확한 아이-높이와 아이-폭 추정 방법

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This paper propose a fast and accurate eye-height and eye-width estimation methods based on deep neural network. The proposed method estimate the eye-height and eye-width fast and accurately by simply reducing the complicated process from design parameters to eye-height and eye-width. Unlike previous methods, the proposed method does not require any additional simulation, so eye-height and eye-width estimation are performed in a few seconds. In addition, various methods were used to optimize the proposed model to lower the error rate and accurately estimate eye-height and eye-width. In this study,the proposed method was applied in PCB size channel and memory channels of HBM interposer. This is a fast and accurate way to estimate eye-height and eye-width of various high-speed channels. At the same time, it is easy to estimate eye-height and eye-width even on channels containing various noises such as crosstalk or ISI. This study was applied to the HBM interposer memory channel and the proposed eye-height and eye-width estimation method of this study is faster and more accurate than the previous eye-height and eye-width estimation methods.
Advisors
Kim, Jounghoresearcher김정호researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.2,[iv, 37 p. :]

Keywords

Machine learning▼adeep neural network▼aeye diagram estimation▼asignal Integrity; 기계 학습▼a딥러닝▼a아이다이어그램 추정▼a신호 무결성

URI
http://hdl.handle.net/10203/266735
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843386&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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