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Neural network based time domain modelling of 0.18 μm MOSFETs
Author(s) -
Toner B.,
Alam M. S.,
Fusco V. F.,
Armstrong G. A.
Publication year - 2002
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.10558
Subject(s) - time domain , mosfet , artificial neural network , waveform , electronic engineering , microwave , signal (programming language) , transistor , electrical engineering , voltage , engineering , computer science , telecommunications , artificial intelligence , computer vision , programming language
In this paper a new time domain based neural network model of a 0.18 μm RF MOSFET will be demonstrated. The model consists of only three intrinsic non‐linear current sources, each being modelled by a neural network derived from large signal time domain voltage/current waveform measurements at the intrinsic device terminals. This approach negates the traditional method of multi‐bias S ‐parameter measurement providing a fast and accurate method of modelling the transistor under large signal conditions. Full verification of the model will be provided against an 80 μm/0.18 μm MOSFET operating at 2.4 GHz. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 35: 203–206, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10558