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A novel methodology to create generative statistical models of interconnects

Simon De Ridder (UGent) , Paolo Manfredi (UGent) , Jan De Geest, Tom Dhaene (UGent) , Daniël De Zutter (UGent) and Dries Vande Ginste (UGent)
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Abstract
This paper addresses the problem of constructing a generative statistical model for an interconnect starting from a limited set of S-parameter samples, which are obtained by simulating or measuring the interconnect for a few random realizations of its stochastic physical properties. These original samples are first converted into a pole-residue representation with common poles. The corresponding residues are modeled as a correlated stochastic process by means of principal component analysis and kernel density estimation. The obtained model allows generating new samples with similar statistics as the original data. A passivity check is performed over the generated samples to retain only passive data. The proposed approach is applied to a representative coupled microstrip line example.
Keywords
Statistical model, interconnect, Principal Com- ponent Analysis, Kernel Density Estimation

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MLA
De Ridder, Simon, Paolo Manfredi, Jan De Geest, et al. “A Novel Methodology to Create Generative Statistical Models of Interconnects.” 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS). IEEE, 2016. 69–71. Print.
APA
De Ridder, Simon, Manfredi, P., De Geest, J., Dhaene, T., De Zutter, D., & Vande Ginste, D. (2016). A novel methodology to create generative statistical models of interconnects. 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS) (pp. 69–71). Presented at the 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), IEEE.
Chicago author-date
De Ridder, Simon, Paolo Manfredi, Jan De Geest, Tom Dhaene, Daniël De Zutter, and Dries Vande Ginste. 2016. “A Novel Methodology to Create Generative Statistical Models of Interconnects.” In 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), 69–71. IEEE.
Chicago author-date (all authors)
De Ridder, Simon, Paolo Manfredi, Jan De Geest, Tom Dhaene, Daniël De Zutter, and Dries Vande Ginste. 2016. “A Novel Methodology to Create Generative Statistical Models of Interconnects.” In 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), 69–71. IEEE.
Vancouver
1.
De Ridder S, Manfredi P, De Geest J, Dhaene T, De Zutter D, Vande Ginste D. A novel methodology to create generative statistical models of interconnects. 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS). IEEE; 2016. p. 69–71.
IEEE
[1]
S. De Ridder, P. Manfredi, J. De Geest, T. Dhaene, D. De Zutter, and D. Vande Ginste, “A novel methodology to create generative statistical models of interconnects,” in 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), Honolulu, 2016, pp. 69–71.
@inproceedings{8520528,
  abstract     = {This paper addresses the problem of constructing a generative statistical model for an interconnect starting from a limited set of S-parameter samples, which are obtained by simulating or measuring the interconnect for a few random realizations of its stochastic physical properties. These original samples are first converted into a pole-residue representation with common poles. The corresponding residues are modeled as a correlated stochastic process by means of 
 principal component analysis and kernel density estimation. The obtained model allows generating new samples with similar statistics as the original data. A passivity check is performed over the generated samples to retain only passive data. The proposed approach is applied to a representative coupled microstrip line example.},
  author       = {De Ridder, Simon and Manfredi, Paolo and De Geest, Jan and Dhaene, Tom and De Zutter, Daniël and Vande Ginste, Dries},
  booktitle    = {2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS)},
  keywords     = {Statistical model,interconnect,Principal Com- ponent Analysis,Kernel Density Estimation},
  language     = {eng},
  location     = {Honolulu},
  pages        = {69--71},
  publisher    = {IEEE},
  title        = {A novel methodology to create generative statistical models of interconnects},
  url          = {http://dx.doi.org/10.1109/edaps.2016.7893128},
  year         = {2016},
}

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