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Dissertations / Theses on the topic 'Augmented Krylov Model Order Reduction'

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Published: 6 September 2023

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1

Olsson, K. Henrik A. "Model Order Reduction with Rational Krylov Methods." Doctoral thesis, Stockholm, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-401.

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2

Maciver, Mark Alasdair. "Electromagnetic characterisation of structures using Krylov subspace model order reduction methods." Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433619.

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3

Agbaje, Oluwaleke Abimbola. "Krylov subspace model order reduction for nonlinear and bilinear control systems." Thesis, Coventry University, 2016. http://curve.coventry.ac.uk/open/items/62c3a18c-4d39-4397-9684-06d77b9cd187/1.

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The use of Krylov subspace model order reduction for nonlinear/bilinear systems, over the past few years, has become an increasingly researched area of study. The need for model order reduction has never been higher, as faster computations for control, diagnosis and prognosis have never been higher to achieve better system performance. Krylov subspace model order reduction techniques enable this to be done more quickly and efficiently than what can be achieved at present. The most recent advances in the use of Krylov subspaces for reducing bilinear models match moments and multimoments at some
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4

Yan, Boyuan. "Advanced non-Krylov subspace model order reduction techniques for interconnect circuits." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://proquest.umi.com/pqdweb?index=0&did=1957340951&SrchMode=2&sid=4&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268670715&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.<br>Includes abstract. Available via ProQuest Digital Dissertations. Title from first page of PDF file (viewed March 12, 2010). Includes bibliographical references (p. 122-126). Also issued in print.
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5

Barkouki, Houda. "Rational Lanczos-type methods for model order reduction." Thesis, Littoral, 2016. http://www.theses.fr/2016DUNK0440/document.

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La solution numérique des systèmes dynamiques est un moyen efficace pour étudier des phénomènes physiques complexes. Cependant, dans un cadre à grande échelle, la dimension du système rend les calculs infaisables en raison des limites de mémoire et de temps, ainsi que le mauvais conditionnement. La solution de ce problème est la réduction de modèles. Cette thèse porte sur les méthodes de projection pour construire efficacement des modèles d'ordre inférieur à partir des systèmes linéaires dynamiques de grande taille. En particulier, nous nous intéressons à la projection sur la réunion de plusie
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6

Wyatt, Sarah Alice. "Issues in Interpolatory Model Reduction: Inexact Solves, Second-order Systems and DAEs." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27668.

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Dynamical systems are mathematical models characterized by a set of differential or difference equations. Model reduction aims to replace the original system with a reduced system of significantly smaller dimension that still describes the important dynamics of the large-scale model. Interpolatory model reduction methods define a reduced model that interpolates the full model at selected interpolation points. The reduced model may be obtained through a Krylov reduction process or by using the Iterative Rational Krylov Algorithm (IRKA), which iterates this Krylov reduction process to obtain an
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7

Hijazi, Abdallah. "Implementation of harmonic balance reduce model order equation." Thesis, Limoges, 2015. http://www.theses.fr/2015LIMO0139/document.

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MOR (Model Order Reduction) est devenu un domaine très répondu dans la recherche grâce à l'intérêt qu'il peut apporter dans la réduction des systèmes, ce qui permet d'économiser du temps, de la mémoire et le coût de CPU pour les outils de CAO. Ce domaine contient principalement deux branches: linéaires et non linéaires. MOR linéaire est un domaine mature avec des techniques numériques bien établie et bien connus dans la domaine de la recherche, par contre le domaine non linéaire reste vague, et jusqu'à présent il n'a pas montré des bons résultats dans la simulation des circuits électriques. La
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8

Panzer, Heiko [Verfasser]. "Model Order Reduction by Krylov Subspace Methods with Global Error Bounds and Automatic Choice of Parameters / Heiko Panzer." München : Verlag Dr. Hut, 2014. http://d-nb.info/1063222176/34.

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9

Panzer, Heiko K. F. [Verfasser], Boris [Akademischer Betreuer] Lohmann, and Athanasios C. [Akademischer Betreuer] Antoulas. "Model Order Reduction by Krylov Subspace Methods with Global Error Bounds and Automatic Choice of Parameters / Heiko K. F. Panzer. Gutachter: Athanasios C. Antoulas ; Boris Lohmann. Betreuer: Boris Lohmann." München : Universitätsbibliothek der TU München, 2014. http://d-nb.info/1064976263/34.

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10

Panzer, Heiko [Verfasser], Boris [Akademischer Betreuer] Lohmann, and Athanasios C. [Akademischer Betreuer] Antoulas. "Model Order Reduction by Krylov Subspace Methods with Global Error Bounds and Automatic Choice of Parameters / Heiko K. F. Panzer. Gutachter: Athanasios C. Antoulas ; Boris Lohmann. Betreuer: Boris Lohmann." München : Universitätsbibliothek der TU München, 2014. http://nbn-resolving.de/urn:nbn:de:bvb:91-diss-20140916-1207822-0-0.

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11

Bernstein, David. "Entwurf einer fehlerüberwachten Modellreduktion basierend auf Krylov-Unterraumverfahren und Anwendung auf ein strukturmechanisches Modell." Master's thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-151975.

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Die FEM-MKS-Kopplung erfordert Modellordnungsreduktions-Verfahren, die mit kleiner reduzierter Systemdimension das Übertragungsverhalten mechanischer Strukturen abbilden. Rationale Krylov-Unterraum-Verfahren, basierend auf dem Arnoldi-Algorithmen, ermöglichen solche Abbildungen in frei wählbaren, breiten Frequenzbereichen. Ziel ist der Entwurf einer fehlerüberwachten Modelreduktion auf Basis von Krylov-Unterraumverfahren und Anwendung auf ein strukturmechanisches Model. Auf Grundlage der Software MORPACK wird eine Arnoldi-Funktion erster Ordnung um interpolativen Startvektor, Eliminierung der
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12

Kumar, Neeraj. "Finite Element Method based Model Order Reduction for Electromagnetics." Thesis, 2016. https://etd.iisc.ac.in/handle/2005/4926.

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Model order reduction (MOR) refers to the process of reducing the size of large scale discrete systems with the goal of capturing their behavior in a small and tractable model known as the reduced order model (ROM). ROMs are invariably constructed by projecting the original system onto a low rank subspace that captures the physics for specified range/s of parameter/s. The parameters, say for electromagnetic scattering, can be the frequency of excitation, angle of incidence, and/or material parameters. Thus, ROMs enable fast parameter sweep analysis and quick prototyping. Historically, a major
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13

Rewieński, Michał. "A Trajectory Piecewise-Linear Approach to Model Order Reduction and Fast Simulation of Nonlinear Circuits and Micromachined Devices." 2002. http://hdl.handle.net/1721.1/4020.

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In this paper we present an approach to the nonlinear model reduction based on representing the nonlinear system with a piecewise-linear system and then reducing each of the pieces with a Krylov projection. However, rather than approximating the individual components to make a system with exponentially many different linear regions, we instead generate a small set of linearizations about the state trajectory which is the response to a 'training input'. Computational results and performance data are presented for a nonlinear circuit and a micromachined fixed-fixed beam example. These example
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14

Milind, R. "Clustering for Model Reduction of Circuits : Multi-level Techniques." Thesis, 2014. http://etd.iisc.ac.in/handle/2005/2774.

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Miniaturisation of electronic chips poses challenges at the design stage. The progressively decreasing circuit dimensions result in complex electrical behaviour that necessitates complex models. Simulation of complex circuit models involves extraordinarily large compu- tational complexity. Such complexity is better managed through Model Order Reduction. Model order reduction has been successful in large reductions in system order for most types of circuits, at high levels of accuracy. However, multiport circuits with large number of inputs/outputs, pose an additional computational challenge. A
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15

Milind, R. "Clustering for Model Reduction of Circuits : Multi-level Techniques." Thesis, 2014. http://hdl.handle.net/2005/2774.

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Miniaturisation of electronic chips poses challenges at the design stage. The progressively decreasing circuit dimensions result in complex electrical behaviour that necessitates complex models. Simulation of complex circuit models involves extraordinarily large compu- tational complexity. Such complexity is better managed through Model Order Reduction. Model order reduction has been successful in large reductions in system order for most types of circuits, at high levels of accuracy. However, multiport circuits with large number of inputs/outputs, pose an additional computational challenge. A
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16

Rother, Stephan. "Modellreduktion thermischer Felder unter Berücksichtigung der Wärmestrahlung." 2019. https://tud.qucosa.de/id/qucosa%3A36164.

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Transiente Simulationen im Rahmen von Parameterstudien oder Optimierungsprozessen erfor-dern die Anwendung der Modellordnungsreduktion zur Minimierung der Berechnungs¬zeiten. Die aus der Wärmestrahlung resultierende Nichtlinearität bei der Analyse thermischer Felder wird hier als äußere Last betrachtet, wodurch die entkoppelte Ermittlung der strahlungs-beding¬ten Wärmeströme gelingt. Darüber hinaus ermöglichen die infolgedessen konstanten System¬matrizen die Reduktion des Temperaturvektors mit etablierten Verfahren für lineare Systeme, wie beispielsweise den Krylov-Unterraummethoden. Die aus d
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17

Mukherjee, Parijat 1985. "Automatic Stability Checking for Large Analog Circuits." Thesis, 2010. http://hdl.handle.net/1969.1/148461.

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Small signal stability has always been an important concern for analog designers. Recent advances such as the Loop Finder algorithm allows designers to detect and identify local, potentially unstable return loops without the need to identify and add breakpoints. However, this method suffers from extremely high time and memory complexity and thus cannot be scaled to very large analog circuits. In this research work, we first take an in-depth look at the loop finder algorithm so as to identify certain key enhancements that can be made to overcome these shortcomings. We next propose pole discover
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