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Hybrid nonlinear modeling using adaptive sampling

Pawel Barmuta, Gustavo Avolio, Francesco Ferranti, Arkadiusz Lewandowski, Luc Knockaert (UGent) and Dominique Schreurs
(2015) IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. 63(12). p.4501-4510
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Abstract
This paper proposes a direct method for the extraction of empirical-behavioral hybrid models using adaptive sampling. The empirical base is responsible for the functionality over a wide range of variables, especially in the extrapolation range. The behavioral part corrects the errors of the empirical part in the region of particular interest, thus, it improves the accuracy in the desired region. Employment of response surface methodology and adaptive sampling allows full automation of the hybrid model extraction and assures its compactness. We used this approach to build a hybrid model composed of a robust empirical model available in CAD tools and a Radial Basis Functions interpolation model with Gaussian basis function. We extracted the hybrid model from measurements of a 0.15 mu m GaAs HEMT and compared it with the pure behavioral and pure empirical models. The hybrid model yields higher accuracy while maintaining extrapolation capabilities. Additionally, the extraction time of the hybrid model is relatively low. We also show that a good accuracy level can be achieved with a small number of measurements.
Keywords
experimental design, TRENDS, response surface, adaptive sampling, behavioral modeling, Active device modeling, DESIGN, DEVICES, BEHAVIORAL-MODELS

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Citation

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MLA
Barmuta, Pawel, et al. “Hybrid Nonlinear Modeling Using Adaptive Sampling.” IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, vol. 63, no. 12, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2015, pp. 4501–10, doi:10.1109/TMTT.2015.2495124.
APA
Barmuta, P., Avolio, G., Ferranti, F., Lewandowski, A., Knockaert, L., & Schreurs, D. (2015). Hybrid nonlinear modeling using adaptive sampling. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 63(12), 4501–4510. https://doi.org/10.1109/TMTT.2015.2495124
Chicago author-date
Barmuta, Pawel, Gustavo Avolio, Francesco Ferranti, Arkadiusz Lewandowski, Luc Knockaert, and Dominique Schreurs. 2015. “Hybrid Nonlinear Modeling Using Adaptive Sampling.” IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 63 (12): 4501–10. https://doi.org/10.1109/TMTT.2015.2495124.
Chicago author-date (all authors)
Barmuta, Pawel, Gustavo Avolio, Francesco Ferranti, Arkadiusz Lewandowski, Luc Knockaert, and Dominique Schreurs. 2015. “Hybrid Nonlinear Modeling Using Adaptive Sampling.” IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 63 (12): 4501–4510. doi:10.1109/TMTT.2015.2495124.
Vancouver
1.
Barmuta P, Avolio G, Ferranti F, Lewandowski A, Knockaert L, Schreurs D. Hybrid nonlinear modeling using adaptive sampling. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES. 2015;63(12):4501–10.
IEEE
[1]
P. Barmuta, G. Avolio, F. Ferranti, A. Lewandowski, L. Knockaert, and D. Schreurs, “Hybrid nonlinear modeling using adaptive sampling,” IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, vol. 63, no. 12, pp. 4501–4510, 2015.
@article{7057253,
  abstract     = {{This paper proposes a direct method for the extraction of empirical-behavioral hybrid models using adaptive sampling. The empirical base is responsible for the functionality over a wide range of variables, especially in the extrapolation range. The behavioral part corrects the errors of the empirical part in the region of particular interest, thus, it improves the accuracy in the desired region. Employment of response surface methodology and adaptive sampling allows full automation of the hybrid model extraction and assures its compactness. We used this approach to build a hybrid model composed of a robust empirical model available in CAD tools and a Radial Basis Functions interpolation model with Gaussian basis function. We extracted the hybrid model from measurements of a 0.15 mu m GaAs HEMT and compared it with the pure behavioral and pure empirical models. The hybrid model yields higher accuracy while maintaining extrapolation capabilities. Additionally, the extraction time of the hybrid model is relatively low. We also show that a good accuracy level can be achieved with a small number of measurements.}},
  author       = {{Barmuta, Pawel and Avolio, Gustavo and Ferranti, Francesco and Lewandowski, Arkadiusz and Knockaert, Luc and Schreurs, Dominique}},
  issn         = {{0018-9480}},
  journal      = {{IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES}},
  keywords     = {{experimental design,TRENDS,response surface,adaptive sampling,behavioral modeling,Active device modeling,DESIGN,DEVICES,BEHAVIORAL-MODELS}},
  language     = {{eng}},
  number       = {{12}},
  pages        = {{4501--4510}},
  publisher    = {{IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC}},
  title        = {{Hybrid nonlinear modeling using adaptive sampling}},
  url          = {{http://doi.org/10.1109/TMTT.2015.2495124}},
  volume       = {{63}},
  year         = {{2015}},
}
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