Hybrid Nonlinear Modeling Using Adaptive Sampling,
Paweł Barmuta , G Avolio , F. Ferranti , Arkadiusz Lewandowski , Luc Knockaert , Dominique M. M.-P. Schreurs
AbstractThis 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 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.
|Journal series||IEEE Transactions on Microwave Theory and Techniques, ISSN 0018-9480, (A 35 pkt)|
|Publication size in sheets||225.05|
|Keywords in English||Active device modeling, adaptive sampling, behavioral modeling, experimental design, response surface|
|ASJC Classification||; ;|
|Score|| = 35.0, 10-03-2019, ArticleFromJournal|
= 35.0, 10-03-2019, ArticleFromJournal
|Publication indicators||: 2017 = 1.956; : 2015 = 2.284 (2) - 2015=2.36 (5)|
|Citation count*||4 (2019-04-15)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.