Title
Single-input-single-output passive macromodeling via Positive Fractions Vector Fitting Single-input-single-output passive macromodeling via Positive Fractions Vector Fitting
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
conferenceObject
Publication
New York, N.Y. :IEEE, [*]
Subject
Mathematics
Source (book)
Proceedings of the 12th IEEE Workshop on Signal Propagation on Interconnects, May 12-15, 2008, Avignon, France
ISBN - Hoofdstuk
978-1-4244-2317-0
ISI
000258904100045
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
This paper introduces a constrained Vector Fitting algorithm which can directly identify a passive driving point function (impedance or admittance) from frequency domain data. The proposed Positive Fractions Vector Fitting (PFVF) algorithm formulates the residue identification step as a convex programming problem, while the pole identification step follows the unaltered standard Vector Fitting procedure. A further extension to multi-input-multi-output functions is possible and is under investigation.
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