Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method

Mohamed Sahouli and Anestis Dounavis
Additional contact information
Mohamed Sahouli: Department of Electrical and Computer, Western University, London, ON N6A 3K7, Canada
Anestis Dounavis: Department of Electrical and Computer, Western University, London, ON N6A 3K7, Canada

Energies, 2021, vol. 14, issue 21, 1-11

Abstract: This paper presents the modeling of high speed distributed networks characterized by S-parameters frequency data using the rational Krylov fitting (RKFIT) algorithm. Numerical examples illustrate the effectiveness of the method to compute stable rational approximation that fit given S-parameters data. In addition, it is shown that RKFIT has some advantages when compared to the well-established Vector Fitting (VF) method, such as more accurate fitting, less dependence on the choice of the initial poles of the algorithm, and faster convergence. Numerical examples are implemented using RKFIT and the results are compared with VF and the Loewner Matrix (LM) algorithm.

Keywords: distributed networks; macromodeling; rational approximation; s-parameters; vector fitting (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/21/7318/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/21/7318/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:21:p:7318-:d:671982

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().