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A hybrid integral equation and neural network approach for fast extraction of frequency dependent parameters of multiconductor transmission lines
Author(s) -
Pan G.,
Piel P.,
Gilbert B.
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.10021
Subject(s) - waveform , microwave , computation , artificial neural network , electric power transmission , computer science , transmission (telecommunications) , integral equation , transmission line , physics , algorithm , electronic engineering , topology (electrical circuits) , mathematical analysis , mathematics , electrical engineering , engineering , telecommunications , artificial intelligence , combinatorics , radar
Multiconductor transmission lines (MTL) have been modeled by the distributed parameters R , L , C , and G in many commercial CAD packages, where most of the parameters are assumed to be frequency independent or at most \documentclass{article}\pagestyle{empty}\begin{document}$R\, \propto \,\sqrt{f}$\end{document} . At gigahertz frequencies, such assumptions may introduce significantly large errors in the waveform simulation and timing. In this article, we present a new and fast technique based on a combination of neural network techniques and the integral equation method (IEM) to evaluate frequency dependences accurately, while dramatically reducing the computation time. © 2002 John Wiley & Sons, Inc. Int J RF and Microwave CAE 12: 37–50, 2002.