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A Quasi-Convex Optimization Approach to Parameterized Model Order Reduction
Electrical Engineering and Computer Science, Massachusetts Institute of Technology.
Electrical Engineering and Computer Science, Massachusetts Institute of Technology.
Electrical Engineering and Computer Science, Massachusetts Institute of Technology.
2008 (English)In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ISSN 0278-0070, E-ISSN 1937-4151, Vol. 27, no 3, 456-469 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, an optimization-based model orderreduction (MOR) framework is proposed. The method involvessetting up a quasi-convex program that solves a relaxation of theoptimal H∞ norm MOR problem. The method can generate guaranteedstable and passive reduced models and is very flexible inimposing additional constraints such as exact matching of specificfrequency response samples. The proposed optimization-basedapproach is also extended to solve the parameterized modelreductionproblem (PMOR). The proposed method is compared to existing moment matching and optimization-basedMOR methodsin several examples. PMOR models for large RF inductors oversubstrate and power-distribution grid are also constructed.

Place, publisher, year, edition, pages
2008. Vol. 27, no 3, 456-469 p.
Keyword [en]
parameterized model order reduction (PMOR), quasi-convex optimization, RF inductor
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-82423DOI: 10.1109/TCAD.2008.915544ISI: 000253840500005OAI: oai:DiVA.org:kth-82423DiVA: diva2:498224
Note
QC 20120213Available from: 2012-02-11 Created: 2012-02-11 Last updated: 2017-12-07Bibliographically approved

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Sou, Kin Cheong
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