Magnitude Vector Fitting to interval data

Hendrickx, W.; Deschrijver, Dirk; Knockaert, Luc; Dhaene, Tom

doi:10.1016/j.matcom.2009.09.009

Cited by 5 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and computing its coefficients through the Magnitude Vector Fitting algorithm [24], [25]. The (minimum-phase) sensitivity macromodel Ξ(s) is then constructed by extracting the subset of zeros and poles with negative real part from (17).…”

Section: Sensitivity-weighted Passivity Enforcementmentioning

confidence: 99%

Sensitivity-based weighting for passivity enforcement of linear macromodels in power integrity applications

Ubolli¹,

Grivet-Talocia²,

Bandinu³

et al. 2014

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2014

View full text Add to dashboard Cite

The electrical performance of Power Distribution Networks (PDNs) is usually assessed by computing frequency responses through quasi-static or full-wave electromagnetic solvers. Such responses, often available in the scattering form, are then fed to suitable macromodeling algorithms for the extraction of compact reduced-order behavioral models that can be seemlessly simulated in the time domain by standard circuit solvers. Such algorithms perform a rational fitting of the raw scattering responses, followed by a passivity check and enforcement step. The resulting macromodel is typically very accurate when compared to the raw scattering responses. It may however happen that the responses of the PDN macromodel exhibit significant deviation from the true system responses under realistic loading conditions, which include appropriate models for active device blocks, decoupling capacitors, voltage regulators, etc. We highlight the source of this accuracy loss, and we propose a sensitivitybased weighting strategy that is able to optimize and tune the macromodel accuracy based on its specific nominal termination network. The particular focus of this paper is the definition and the inclusion of optimal weigths in the passivity enforcement loop, which is recognized as the most challenging step. The result is a reliable macromodeling flow, which is able to produce passive, accurate and efficient reduced-order models of general PDN structures for power integrity analysis and verification.

show abstract

Section: Sensitivity-weighted Passivity Enforcementmentioning

confidence: 99%

Sensitivity-based weighting for passivity enforcement of linear macromodels in power integrity applications

Ubolli¹,

Grivet-Talocia²,

Bandinu³

et al. 2014

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2014

View full text Add to dashboard Cite

show abstract

“…Examples of frequency-sampled data are scattering parameters (S-parameters) for RF objects and admittance parameters (Y -parameters) for interconnects. Alternative data choices, such as frequency response derivative H ′ (s) [20], phase response ∠H (s) [21] and magnitude response |H (s)| [22], are used for different identification purposes. In practices, frequency-domain macromodeling involves complicated measurements.…”

Section: Data: Input Data Choicesmentioning

confidence: 99%

A Decade of Vector Fitting Development: Applications on Signal∕Power Integrity

Lei

Wang

Chen

et al. 2010

AIP Conference Proceedings

View full text Add to dashboard Cite

Vector Fitting (VF) has been introduced as a partial-fraction basis response fitting methodology for over a decade. Because of its reliability and versatility, VF has been applied and extended to a number of areas. In this book chapter, we will discuss the applications of VF in the context of macromodeling of linear structures in signal/power integrity analyses. We will also discuss main features of VF along three directions: data, algorithms and models. Two practical examples are given to demonstrate the merits of VF. An alternative P-norm approximation criterion is proposed to enhance the accuracy of the macromodeling process.

show abstract

Magnitude-only modeling for sigma-delta modulator characterization

Touloupas

Sotiriadis

2019

AEU - International Journal of Electronics and Communications

View full text Add to dashboard Cite

Magnitude Vector Fitting to interval data

Cited by 5 publications

References 18 publications

Sensitivity-based weighting for passivity enforcement of linear macromodels in power integrity applications

Sensitivity-based weighting for passivity enforcement of linear macromodels in power integrity applications

A Decade of Vector Fitting Development: Applications on Signal∕Power Integrity

Magnitude-only modeling for sigma-delta modulator characterization

Contact Info

Product

Resources

About