Výsledky vyhledávání - "Patrick Kürschner"

Approximate residual-minimizing shift parameters for the low-rank ADI iteration

Autor: Patrick Kürschner

Publikováno v: ETNA - Electronic Transactions on Numerical Analysis. 51:240-261

preprint at https://arxiv.org/abs/1811.05500 ispartof: ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS vol:51 pages:240-261 status: Published online

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::575aa57efb4313424c00bac61b05b897
https://doi.org/10.1553/etna_vol51s240

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Combined error estimates for local fluctuations of SPDEs

Autor: Christian Kuehn, Patrick Kürschner

Publikováno v: Advances in Computational Mathematics. 46

In this work, we study the numerical approximation of local fluctuations of certain classes of parabolic stochastic partial differential equations (SPDEs). Our focus is on effects for small spatially-correlated noise on a time scale before large devi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9399542320928c485793aaeceb5366b8
https://doi.org/10.1007/s10444-020-09766-2

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RADI: a low-rank ADI-type algorithm for large scale algebraic Riccati equations

Autor: Jens Saak, Patrick Kürschner, Zvonimir Bujanović, Peter Benner

Publikováno v: Numerische Mathematik

In recent years, several new approaches for solving the large-scale continuous-time algebraic Riccati equation have appeared in the literature. Amodei and Buchot suggest computing a low-dimensional invariant subspace of the associated Hamiltonian mat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1da331ee2aa86bbda2998fea0cd09148
https://doi.org/10.1007/s00211-017-0907-5

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Greedy low-rank algorithm for spatial connectome regression

Autor: Patrick Kürschner, Kameron Decker Harris, Sergey Dolgov, Peter Benner

Publikováno v: Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience, Vol 9, Iss 1, Pp 1-22 (2019)
The Journal of Mathematical Neuroscience

Recovering brain connectivity from tract tracing data is an important computational problem in the neurosciences. Mesoscopic connectome reconstruction was previously formulated as a structured matrix regression problem (Harris et al. in Neural Inform

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4ad190e61cbfd42c599f35965fcfd9a
https://lirias.kuleuven.be/handle/123456789/644997

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On the convergence of Krylov methods with low-rank truncations

Autor: Patrick Kürschner, Davide Palitta

Publikováno v: Numerical Algorithms

Low-rank Krylov methods are one of the few options available in the literature to address the numerical solution of large-scale general linear matrix equations. These routines amount to well-known Krylov schemes that have been equipped with a couple

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48322875828aac13cba2ffe418fe9ed1
http://arxiv.org/abs/1909.01226

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Low-rank updates and divide-and-conquer methods for quadratic matrix equations

Autor: Patrick Kürschner, Daniel Kressner, Stefano Massei

In this work, we consider two types of large-scale quadratic matrix equations: continuous-time algebraic Riccati equations, which play a central role in optimal and robust control, and unilateral quadratic matrix equations, which arise from stochasti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95312e79d811b47084ed5fcad3056c05
http://arxiv.org/abs/1903.02343

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Low-rank Newton-ADI methods for large nonsymmetric algebraic Riccati equations

Autor: Patrick Kürschner, Peter Benner, Jens Saak

Publikováno v: Journal of the Franklin Institute. 353:1147-1167

The numerical treatment of large-scale, nonsymmetric algebraic Riccati equations (NAREs) by a low-rank variant of Newton׳s method is considered. We discuss a method to compute approximations to the solution of the NARE in a factorized form of low ra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::16ec00820cbcc386e6a49b608642ff63
https://doi.org/10.1016/j.jfranklin.2015.04.016

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Numerical computation and new output bounds for time-limited balanced truncation of discrete-time systems

Autor: Patrick Kürschner, Igor Pontes Duff

Publikováno v: Linear Algebra and its Applications

In this paper, balancing based model order reduction (MOR) for large-scale linear discrete-time time-invariant systems in prescribed finite time intervals is studied. The first main topic is the development of error bounds regarding the approximated

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A numerical comparison of solvers for large-scale, continuous-time algebraic Riccati equations and LQR problems

Autor: Zvonimir Bujanović, Jens Saak, Patrick Kürschner, Peter Benner

Publikováno v: SIAM Journal on Scientific Computing

In this paper, we discuss numerical methods for solving large-scale continuous-time algebraic Riccati equations. These methods have been the focus of intensive research in recent years, and significant progress has been made in both the theoretical u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdb339a08f7b7d3824cfa7af77a09535
http://arxiv.org/abs/1811.00850

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