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Stochastic macromodeling for hierarchical uncertainty quantification of nonlinear electronic systems

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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.
Keywords
TRANSFER-FUNCTION TRAJECTORIES, IBCN, POLYNOMIAL-CHAOS EXPANSION, VARIABILITY ANALYSIS, CIRCUITS

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Citation

Please use this url to cite or link to this publication:

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.
@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},
}

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