Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method

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 dat...

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Autores principales:	Mohamed Sahouli, Anestis Dounavis
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	distributed networks macromodeling rational approximation s-parameters vector fitting Technology T
Acceso en línea:	https://doaj.org/article/f84bf4e4ca334491b67ef29e73c0fbd4
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id	oai:doaj.org-article:f84bf4e4ca334491b67ef29e73c0fbd4
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spelling	oai:doaj.org-article:f84bf4e4ca334491b67ef29e73c0fbd42021-11-11T16:02:58ZMacromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method10.3390/en142173181996-1073https://doaj.org/article/f84bf4e4ca334491b67ef29e73c0fbd42021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/7318https://doaj.org/toc/1996-1073This 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.Mohamed SahouliAnestis DounavisMDPI AGarticledistributed networksmacromodelingrational approximations-parametersvector fittingTechnologyTENEnergies, Vol 14, Iss 7318, p 7318 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	distributed networks macromodeling rational approximation s-parameters vector fitting Technology T
spellingShingle	distributed networks macromodeling rational approximation s-parameters vector fitting Technology T Mohamed Sahouli Anestis Dounavis Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method
description	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.
format	article
author	Mohamed Sahouli Anestis Dounavis
author_facet	Mohamed Sahouli Anestis Dounavis
author_sort	Mohamed Sahouli
title	Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method
title_short	Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method
title_full	Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method
title_fullStr	Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method
title_full_unstemmed	Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method
title_sort	macromodeling high-speed circuit data using rational krylov fitting method
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f84bf4e4ca334491b67ef29e73c0fbd4
work_keys_str_mv	AT mohamedsahouli macromodelinghighspeedcircuitdatausingrationalkrylovfittingmethod AT anestisdounavis macromodelinghighspeedcircuitdatausingrationalkrylovfittingmethod
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Macromodeling High-Speed Circuit Data Using Rational Krylov Fitting Method

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