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Stochastic macromodeling for hierarchical uncertainty quantification of nonlinear electronic systems

Domenico Spina UGent, D De Jonghe, Francesco Ferranti, G Gielen, Tom Dhaene UGent, Luc Knockaert UGent and G Antonini (2015) IEEE International Symposium on Electromagnetic Compatibility. p.1335-1338
abstract
A hierarchical stochastic macromodeling approach is proposed for the efficient variability analysis of complex nonlinear electronic systems. A combination of the Transfer Function Trajectory and Polynomial Chaos methods is used to generate stochastic macromodels. In order to reduce the computational complexity of the model generation when the number of stochastic variables increases, a hierarchical system decomposition is used. Pertinent numerical results validate the proposed methodology.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
TRANSFER-FUNCTION TRAJECTORIES, IBCN, POLYNOMIAL-CHAOS EXPANSION, VARIABILITY ANALYSIS, CIRCUITS
in
IEEE International Symposium on Electromagnetic Compatibility
issue title
2015 IEEE INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY (EMC)
pages
1335 - 1338
publisher
IEEE
conference name
Joint IEEE International Symposium on Electromagnetic Compatibility (EMC) and EMC Europe
conference location
Dresden, Germany
conference start
2015-08-16
conference end
2015-08-22
Web of Science type
Proceedings Paper
Web of Science id
000370282300241
ISSN
2158-110X
ISBN
978-1-4799-6615-8
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
7239946
handle
http://hdl.handle.net/1854/LU-7239946
date created
2016-06-01 10:17:39
date last changed
2016-12-19 15:37:16
@inproceedings{7239946,
  abstract     = {A hierarchical stochastic macromodeling approach is proposed for the efficient variability analysis of complex nonlinear electronic systems. A combination of the Transfer Function Trajectory and Polynomial Chaos methods is used to generate stochastic macromodels. In order to reduce the computational complexity of the model generation when the number of stochastic variables increases, a hierarchical system decomposition is used. Pertinent numerical results validate the proposed methodology.},
  author       = {Spina, Domenico and De Jonghe, D and Ferranti, Francesco and Gielen, G and Dhaene, Tom and Knockaert, Luc and Antonini, G},
  booktitle    = {IEEE International Symposium on Electromagnetic Compatibility},
  isbn         = {978-1-4799-6615-8},
  issn         = {2158-110X},
  keyword      = {TRANSFER-FUNCTION TRAJECTORIES,IBCN,POLYNOMIAL-CHAOS EXPANSION,VARIABILITY ANALYSIS,CIRCUITS},
  language     = {eng},
  location     = {Dresden, Germany},
  pages        = {1335--1338},
  publisher    = {IEEE},
  title        = {Stochastic macromodeling for hierarchical uncertainty quantification of nonlinear electronic systems},
  year         = {2015},
}

Chicago
Spina, Domenico, D De Jonghe, Francesco Ferranti, G Gielen, Tom Dhaene, Luc Knockaert, and G Antonini. 2015. “Stochastic Macromodeling for Hierarchical Uncertainty Quantification of Nonlinear Electronic Systems.” In IEEE International Symposium on Electromagnetic Compatibility, 1335–1338. IEEE.
APA
Spina, D., De Jonghe, D., Ferranti, F., Gielen, G., Dhaene, T., Knockaert, L., & Antonini, G. (2015). Stochastic macromodeling for hierarchical uncertainty quantification of nonlinear electronic systems. IEEE International Symposium on Electromagnetic Compatibility (pp. 1335–1338). Presented at the Joint IEEE International Symposium on Electromagnetic Compatibility (EMC) and EMC Europe, IEEE.
Vancouver
1.
Spina D, De Jonghe D, Ferranti F, Gielen G, Dhaene T, Knockaert L, et al. Stochastic macromodeling for hierarchical uncertainty quantification of nonlinear electronic systems. IEEE International Symposium on Electromagnetic Compatibility. IEEE; 2015. p. 1335–8.
MLA
Spina, Domenico, D De Jonghe, Francesco Ferranti, et al. “Stochastic Macromodeling for Hierarchical Uncertainty Quantification of Nonlinear Electronic Systems.” IEEE International Symposium on Electromagnetic Compatibility. IEEE, 2015. 1335–1338. Print.