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Adaptive frequency sampling using linear Bayesian vector fitting

Simon De Ridder (UGent) , Dirk Deschrijver (UGent) , Domenico Spina (UGent) , Tom Dhaene (UGent) and Dries Vande Ginste (UGent)
(2019) ELECTRONICS LETTERS. 55(2). p.74-76
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Abstract
The authors present a novel Bayesian approach to adaptively select frequency samples to obtain a rational macromodel of device responses over a broad frequency range while performing as few electromagnetic simulations as possible. The method leverages a Bayesian approach to vector fitting to construct a data-driven uncertainty measure. The presented technique is demonstrated by application to a double semi-circular patch antenna and is shown to accurately and efficiently construct a rational macromodel over the frequency range of interest.
Keywords
ALGORITHM, Bayes methods, microstrip antennas, vectors, electromagnetic, simulations, double semicircular patch antenna, rational macromodel, adaptive frequency sampling, adaptively select frequency samples, linear, Bayesian vector fitting approach, measurement uncertainty

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Citation

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

Chicago
De Ridder, Simon, Dirk Deschrijver, Domenico Spina, Tom Dhaene, and Dries Vande Ginste. 2019. “Adaptive Frequency Sampling Using Linear Bayesian Vector Fitting.” Electronics Letters 55 (2): 74–76.
APA
De Ridder, Simon, Deschrijver, D., Spina, D., Dhaene, T., & Vande Ginste, D. (2019). Adaptive frequency sampling using linear Bayesian vector fitting. ELECTRONICS LETTERS, 55(2), 74–76.
Vancouver
1.
De Ridder S, Deschrijver D, Spina D, Dhaene T, Vande Ginste D. Adaptive frequency sampling using linear Bayesian vector fitting. ELECTRONICS LETTERS. Hertford: Inst Engineering Technology-iet; 2019;55(2):74–6.
MLA
De Ridder, Simon et al. “Adaptive Frequency Sampling Using Linear Bayesian Vector Fitting.” ELECTRONICS LETTERS 55.2 (2019): 74–76. Print.
@article{8601118,
  abstract     = {The authors present a novel Bayesian approach to adaptively select frequency samples to obtain a rational macromodel of device responses over a broad frequency range while performing as few electromagnetic simulations as possible. The method leverages a Bayesian approach to vector fitting to construct a data-driven uncertainty measure. The presented technique is demonstrated by application to a double semi-circular patch antenna and is shown to accurately and efficiently construct a rational macromodel over the frequency range of interest.},
  author       = {De Ridder, Simon and Deschrijver, Dirk and Spina, Domenico and Dhaene, Tom and Vande Ginste, Dries},
  issn         = {0013-5194},
  journal      = {ELECTRONICS LETTERS},
  language     = {eng},
  number       = {2},
  pages        = {74--76},
  publisher    = {Inst Engineering Technology-iet},
  title        = {Adaptive frequency sampling using linear Bayesian vector fitting},
  url          = {http://dx.doi.org/10.1049/el.2018.6668},
  volume       = {55},
  year         = {2019},
}

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