We introduce a multivariate adaptive sampling algorithm for the passivity characterization of parameterized macromodels. The proposed approach builds on existing sampling methods based on adaptive frequency warping for tracking pole-induced variability of passivity metrics, which however are available only for univariate (non-parameterized) models. Here, we extend this approach to the more challenging parameterized setting, where model poles hence passivity violations depend on possibly several external parameters embedded in the macro-model. Numerical examples show excellent performance and speedup with respect to competing approaches.

A Multivariate Adaptive Sampling Scheme for Passivity Characterization of Parameterized Macromodels / De Stefano, Marco; Grivet-Talocia, Stefano. - ELETTRONICO. - (2021), pp. 1-3. ((Intervento presentato al convegno 2021 IEEE 25th Workshop on Signal and Power Integrity (SPI) tenutosi a Virtual conference nel 10-12 May 2021 [10.1109/SPI52361.2021.9505207].

A Multivariate Adaptive Sampling Scheme for Passivity Characterization of Parameterized Macromodels

De Stefano, Marco;Grivet-Talocia, Stefano
2021

Abstract

We introduce a multivariate adaptive sampling algorithm for the passivity characterization of parameterized macromodels. The proposed approach builds on existing sampling methods based on adaptive frequency warping for tracking pole-induced variability of passivity metrics, which however are available only for univariate (non-parameterized) models. Here, we extend this approach to the more challenging parameterized setting, where model poles hence passivity violations depend on possibly several external parameters embedded in the macro-model. Numerical examples show excellent performance and speedup with respect to competing approaches.
978-1-6654-2388-5
File in questo prodotto:
File Dimensione Formato  
cnf-2021-spi-sampling-ieee.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 1.87 MB
Formato Adobe PDF
1.87 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
cnf-2021-spi-sampling.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 479.02 kB
Formato Adobe PDF
479.02 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2920772