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Process Proximity correction by using neural networks

Title
Process Proximity correction by using neural networks
Author
오혜근
Issue Date
2002-11
Publisher
IEEE
Citation
2002 International Microprocesses and Nanotechnology Conference, 2002. Digest of Papers., page. 256-257
Abstract
Making an accurate and quick critical dimension (CD) prediction is required for higher integrated device. Because simulation tools are consisted of many process parameters and models, it is hard that process parameters are calibrated to match with the CD results for various patterns. This paper presents a method of improving accuracy of predicting CD results by applying /spl Delta/ (the difference between simulation and experimental data) value to neural network algorithm (NNA) to reduce CD the difference caused by optical proximity effect.
URI
https://ieeexplore.ieee.org/document/1178640?arnumber=1178640&SID=EBSCO:edseeehttps://repository.hanyang.ac.kr/handle/20.500.11754/157873
ISBN
4-89114-031-3
DOI
10.1109/IMNC.2002.1178640
Appears in Collections:
COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E](과학기술융합대학) > APPLIED PHYSICS(응용물리학과) > Articles
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