Bibliografías temáticas / Jacobi-Davidson Iteration

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Literatura académica sobre el tema "Jacobi-Davidson Iteration"

Autor: Grafiati
Publicado: 6 de septiembre de 2023

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Artículos de revistas sobre el tema "Jacobi-Davidson Iteration"

1

Zhao, Jutao, and Pengfei Guo. "A Study on the Convergence Analysis of the Inexact Simplified Jacobi–Davidson Method." Journal of Mathematics 2021 (December 7, 2021): 1–10. http://dx.doi.org/10.1155/2021/2123897.

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The Jacobi–Davidson iteration method is very efficient in solving Hermitian eigenvalue problems. If the correction equation involved in the Jacobi–Davidson iteration is solved accurately, the simplified Jacobi–Davidson iteration is equivalent to the Rayleigh quotient iteration which achieves cubic convergence rate locally. When the involved linear system is solved by an iteration method, these two methods are also equivalent. In this paper, we present the convergence analysis of the simplified Jacobi–Davidson method and present the estimate of iteration numbers of the inner correction equation
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Kong, Yuan, and Yong Fang. "Behavior of the Correction Equations in the Jacobi–Davidson Method." Mathematical Problems in Engineering 2019 (August 5, 2019): 1–4. http://dx.doi.org/10.1155/2019/5169362.

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The Jacobi–Davidson iteration method is efficient for computing several eigenpairs of Hermitian matrices. Although the involved correction equation in the Jacobi–Davidson method has many developed variants, the behaviors of them are not clear for us. In this paper, we aim to explore, theoretically, the convergence property of the Jacobi–Davidson method influenced by different types of correction equations. As a by-product, we derive the optimal expansion vector, which imposed a shift-and-invert transform on a vector located in the prescribed subspace, to expand the current subspace.
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Zhou, Yunkai. "Studies on Jacobi–Davidson, Rayleigh quotient iteration, inverse iteration generalized Davidson and Newton updates." Numerical Linear Algebra with Applications 13, no. 8 (2006): 621–42. http://dx.doi.org/10.1002/nla.490.

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Sleijpen, Gerard L. G., and Henk A. Van der Vorst. "A Jacobi--Davidson Iteration Method for Linear Eigenvalue Problems." SIAM Review 42, no. 2 (2000): 267–93. http://dx.doi.org/10.1137/s0036144599363084.

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G. Sleijpen, Gerard L., and Henk A. Van der Vorst. "A Jacobi–Davidson Iteration Method for Linear Eigenvalue Problems." SIAM Journal on Matrix Analysis and Applications 17, no. 2 (1996): 401–25. http://dx.doi.org/10.1137/s0895479894270427.

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Freitag, M. A., and A. Spence. "Rayleigh quotient iteration and simplified Jacobi–Davidson method with preconditioned iterative solves." Linear Algebra and its Applications 428, no. 8-9 (2008): 2049–60. http://dx.doi.org/10.1016/j.laa.2007.11.013.

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Huang, Yin-Liang, Tsung-Ming Huang, Wen-Wei Lin, and Wei-Cheng Wang. "A Null Space Free Jacobi--Davidson Iteration for Maxwell's Operator." SIAM Journal on Scientific Computing 37, no. 1 (2015): A1—A29. http://dx.doi.org/10.1137/140954714.

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Szyld, Daniel B., and Fei Xue. "Efficient Preconditioned Inner Solves For Inexact Rayleigh Quotient Iteration And Their Connections To The Single-Vector Jacobi–Davidson Method." SIAM Journal on Matrix Analysis and Applications 32, no. 3 (2011): 993–1018. http://dx.doi.org/10.1137/100807922.

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Jia, ZhongXiao, and Zhen Wang. "A convergence analysis of the inexact Rayleigh quotient iteration and simplified Jacobi-Davidson method for the large Hermitian matrix eigenproblem." Science in China Series A: Mathematics 51, no. 12 (2008): 2205–16. http://dx.doi.org/10.1007/s11425-008-0050-y.

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Hochstenbach, Michiel E., and Yvan Notay. "Controlling Inner Iterations in the Jacobi–Davidson Method." SIAM Journal on Matrix Analysis and Applications 31, no. 2 (2009): 460–77. http://dx.doi.org/10.1137/080732110.

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Tesis sobre el tema "Jacobi-Davidson Iteration"

1

Freitag, Melina. "Inner-outer iterative methods for eigenvalue problems : convergence and preconditioning." Thesis, University of Bath, 2007. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.512248.

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Many methods for computing eigenvalues of a large sparse matrix involve shift-invert transformations which require the solution of a shifted linear system at each step. This thesis deals with shift-invert iterative techniques for solving eigenvalue problems where the arising linear systems are solved inexactly using a second iterative technique. This approach leads to an inner-outer type algorithm. We provide convergence results for the outer iterative eigenvalue computation as well as techniques for efficient inner solves. In particular eigenvalue computations using inexact inverse iteration,
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2

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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Actas de conferencias sobre el tema "Jacobi-Davidson Iteration"

1

Kumar, Neeraj, K. J. Vinoy, and S. Gopalakrishnan. "Jacobi-Davidson iteration based reduced order finite element models for radar cross-section." In 2013 IEEE Applied Electromagnetics Conference (AEMC). IEEE, 2013. http://dx.doi.org/10.1109/aemc.2013.7045048.

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Kumar, Neeraj, K. J. Vinoy, and S. Gopalakrishnan. "Efficient finite element model order reduction of electromagnetic systems using fast converging Jacobi-Davidson Iteration." In 2014 IEEE International Microwave and RF Conference (IMaRC). IEEE, 2014. http://dx.doi.org/10.1109/imarc.2014.7038957.

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