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Adaptive sampling algorithm for macromodeling of parameterized S-parameter responses

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Abstract
This paper presents a new adaptive sampling strategy for the parametric macromodeling of S-parameter-based frequency responses. It can be linked directly with the simulator to determine up front a sparse set of data samples that characterize the design space. This approach limits the overall simulation and macromodeling time. The resulting sample distribution can be fed into any kind of macromodeling technique, provided that it can deal with scattered data. The effectiveness of the approach is illustrated by a parameterized H-shaped microwave example.
Keywords
parametric macromodel, multivariate model, sequential design, Adaptive sampling, frequency response, FREQUENCY-DOMAIN

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

Chicago
Deschrijver, Dirk, Karel Crombecq, Huu Minh Nguyen, and Tom Dhaene. 2011. “Adaptive Sampling Algorithm for Macromodeling of Parameterized S-parameter Responses.” Ieee Transactions on Microwave Theory and Techniques 59 (1): 39–45.
APA
Deschrijver, D., Crombecq, K., Nguyen, H. M., & Dhaene, T. (2011). Adaptive sampling algorithm for macromodeling of parameterized S-parameter responses. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 59(1), 39–45.
Vancouver
1.
Deschrijver D, Crombecq K, Nguyen HM, Dhaene T. Adaptive sampling algorithm for macromodeling of parameterized S-parameter responses. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. 2011;59(1):39–45.
MLA
Deschrijver, Dirk, Karel Crombecq, Huu Minh Nguyen, et al. “Adaptive Sampling Algorithm for Macromodeling of Parameterized S-parameter Responses.” IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 59.1 (2011): 39–45. Print.
@article{1259567,
  abstract     = {This paper presents a new adaptive sampling strategy for the parametric macromodeling of S-parameter-based frequency responses. It can be linked directly with the simulator to determine up front a sparse set of data samples that characterize the design space. This approach limits the overall simulation and macromodeling time. The resulting sample distribution can be fed into any kind of macromodeling technique, provided that it can deal with scattered data. The effectiveness of the approach is illustrated by a parameterized H-shaped microwave example.},
  author       = {Deschrijver, Dirk and Crombecq, Karel and Nguyen, Huu Minh and Dhaene, Tom},
  issn         = {0018-9480},
  journal      = {IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES},
  keyword      = {parametric macromodel,multivariate model,sequential design,Adaptive sampling,frequency response,FREQUENCY-DOMAIN},
  language     = {eng},
  number       = {1},
  pages        = {39--45},
  title        = {Adaptive sampling algorithm for macromodeling of parameterized S-parameter responses},
  url          = {http://dx.doi.org/10.1109/TMTT.2010.2090407},
  volume       = {59},
  year         = {2011},
}

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