Statistical modeling of frequency responses using linear Bayesian vector fitting. (3rd June 2020)

• Record Type: Journal Article
• Authors: De Ridder, Simon; Deschrijver, Dirk; Spina, Domenico; Vande Ginste, Dries; Dhaene, Tom
• Other Names: Koziel Slawomir guestEditor.; Pietrenko‐Dabrowska Anna guestEditor.
• Is Part Of: International journal of numerical modelling. Volume 33:Number 6(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-03
• Subjects: adaptive sampling -- bayesian inference -- macromodeling; Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2762
• Languages: English
• ISSNs: 0894-3370

Abstract

Abstract: This article presents a Bayesian extension of the vector fitting (VF) procedure for rational approximation of frequency‐domain responses. The proposed method treats the linear part of VF in a Bayesian way, while propagating distributions through the nonlinear part by sampling. As such, it is capable of providing data‐driven uncertainty information along with the rational fit. The Bayesian VF technique is applied to two realistic design examples, a double folded stub filter and a RAM memory channel, demonstrating its validity and highlighting three potential applications of this novel framework.