Single-Input-Single-Output Passive Macromodeling via Positive Fractions Vector Fitting

Author

De Tommasi, Luciano ; Deschrijver, Dirk ; Dhaene, Tom

Author_Institution

Dept. of Math. & Comput. Sci., Antwerp Univ., Antwerp

fYear

2008

fDate

12-15 May 2008

Firstpage

1

Lastpage

2

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.

Keywords

convex programming; passive networks; pole assignment; convex programming problem; multiinput-multioutput functions; passive driving point function; pole identification; positive fractions vector fitting; residue identification step; single-input-single-output passive macromodeling; Admittance; Computer science; Fitting; Frequency domain analysis; Functional programming; Impedance; Information technology; Mathematics; Modems; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Propagation on Interconnects, 2008. SPI 2008. 12th IEEE Workshop on

Conference_Location

Avignon

Print_ISBN

978-1-4244-2317-0

Electronic_ISBN

978-1-4244-2318-7

Type

conf

DOI

10.1109/SPI.2008.4558387

Filename

4558387