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Adaptive sampling algorithm for macromodeling of parameterized S-parameter responses

Dirk Deschrijver UGent, Karel Crombecq, Huu Minh Nguyen UGent and Tom Dhaene UGent (2011) IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. 59(1). p.39-45
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
parametric macromodel, multivariate model, sequential design, Adaptive sampling, frequency response, FREQUENCY-DOMAIN
journal title
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
IEEE Trans. Microw. Theory Tech.
volume
59
issue
1
pages
39 - 45
Web of Science type
Article
Web of Science id
000286109400004
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
1.853 (2011)
JCR rank
55/244 (2011)
JCR quartile
1 (2011)
ISSN
0018-9480
DOI
10.1109/TMTT.2010.2090407
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1259567
handle
http://hdl.handle.net/1854/LU-1259567
date created
2011-06-10 10:57:45
date last changed
2016-12-19 15:45:03
@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},
}

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.