Support Vector Regression-Based Active Subspace (SVR-AS) Modeling of High-Speed Links for Fast and Accurate Sensitivity Analysis-Reference-Cited by-同舟云学术

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Support Vector Regression-Based Active Subspace (SVR-AS) Modeling of High-Speed Links for Fast and Accurate Sensitivity Analysis

Published:2020 Issue: Volume:8 Page:74339-74348
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ma Hanzhi^ORCID,Li Er-Ping^ORCID,Cangellaris Andreas C.,Chen Xu

Funder

National Science Foundation of China

National Science Foundation

Center for Advanced Electronics through Machine Learning (CAEML) and its industry members

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

https://ieeexplore.ieee.org/ielam/6287639/8948470/9068208-aam.pdf

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