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Neural network modeling of microwave FETs based on third‐order distortion characterization
Author(s) -
Giannini F.,
Colantonio P.,
Orengo G.,
Serino A.
Publication year - 2006
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.20138
Subject(s) - intermodulation , volterra series , high electron mobility transistor , distortion (music) , microwave , nonlinear distortion , characterization (materials science) , total harmonic distortion , nonlinear system , electronic engineering , artificial neural network , series (stratigraphy) , tone (literature) , computer science , materials science , engineering , physics , telecommunications , transistor , amplifier , electrical engineering , artificial intelligence , nanotechnology , cmos , art , voltage , literature , biology , paleontology , quantum mechanics
A new method for characterization of HEMT distortion parameters, which extracts the coefficents of a Taylor series expansion of I ds ( V gs , V ds ), including all cross‐terms, is developed from low‐frequency harmonic measurements. The extracted parameters will be used either in a Volterra series model around a fixed bias point for 3 rd ‐order characterization of small‐signal I ds nonlinearity, or in a large‐signal model of I ds characteristic, where its partial derivatives are locally characterized up to the 3 rd order in the whole bias region, using a novel neural‐network representation. The two models are verified by one‐tone and two‐tone intermodulation distortion (IMD) tests on a PHEMT device. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006.