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Small‐signal and large‐signal modeling of active devices using CAD‐optimized neural networks
Author(s) -
Giannini F.,
Leuzzi G.,
Orengo G.,
Albertini M.
Publication year - 2002
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.10007
Subject(s) - mesfet , artificial neural network , microwave , signal (programming language) , electronic engineering , electronic circuit simulation , scattering parameters , equivalent circuit , high electron mobility transistor , computer science , large signal model , cad , noise (video) , integrated circuit , power (physics) , electronic circuit , engineering , electrical engineering , transistor , voltage , telecommunications , artificial intelligence , field effect transistor , physics , quantum mechanics , engineering drawing , image (mathematics) , programming language
Artificial neural networks (ANNs) are presented for the technology‐independent modeling of active devices in MMICs. ANNs trained with S‐parameter and DC measurements over the entire bias and frequency operational band are used for the small‐signal bias‐dependent modeling of a low‐noise GaAs HEMT device, without the need of the equivalent circuit parameter extraction. ANNs are also used within the large‐signal model of a power MESFET device, modeling the drain‐source current I ds and charges Q g and Q d obtained from integration of their partial derivatives. After training and testing, the ANN models have been implemented as two‐port networks into a microwave circuit simulator. This enabled the ANN models to be used in the design, analysis, and optimization of microwave/mm‐wave circuits. Improved techniques in network building to provide not only accurate but also fast simulation models have been applied. © 2002 John Wiley & Sons, Inc. Int J RF and Microwave CAE 12: 71–78, 2002.