TY - GEN
T1 - Efficient Uncertainty Quantification of Stripline Pulse Response using Singular Value Decomposition and Delay Extraction
AU - Page, Andrew
AU - Chen, Xu
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper demonstrates the use of data post-processing methods with stochastic collocation, an efficient alternative to Monte Carlo sampling, for transient response parametrization in electronic design. This method is applied to find the statistics of the broadband voltage response of a 50Ω terminated stripline with uncertain width, length, and per-mittivity. Collocation results with post-processing are compared against that of Monte Carlo showing greater accuracy for a low computational budget.
AB - This paper demonstrates the use of data post-processing methods with stochastic collocation, an efficient alternative to Monte Carlo sampling, for transient response parametrization in electronic design. This method is applied to find the statistics of the broadband voltage response of a 50Ω terminated stripline with uncertain width, length, and per-mittivity. Collocation results with post-processing are compared against that of Monte Carlo showing greater accuracy for a low computational budget.
KW - delay extraction
KW - singular value decomposition
KW - stochastic collocation
UR - http://www.scopus.com/inward/record.url?scp=85139489935&partnerID=8YFLogxK
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U2 - 10.1109/APEMC53576.2022.9888395
DO - 10.1109/APEMC53576.2022.9888395
M3 - Conference contribution
AN - SCOPUS:85139489935
T3 - 2022 Asia-Pacific International Symposium on Electromagnetic Compatibility, APEMC 2022
SP - 4
EP - 6
BT - 2022 Asia-Pacific International Symposium on Electromagnetic Compatibility, APEMC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th Asia-Pacific International Symposium on Electromagnetic Compatibility and Technical Exhibition, APEMC 2022
Y2 - 1 September 2022 through 4 September 2022
ER -