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
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Acceso en línea:https://doaj.org/article/f84bf4e4ca334491b67ef29e73c0fbd4
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Sumario: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.