JDQZ

Matlab® implementation of the JDQZ algorithm. The JDQZ algorithm can be used for computing a few selected eigenvalues with some desirable property together with the associated eigenvectors of a matrix pencil A-lambda*B. The matrices can be real or complex, Hermitian or non-Hermitian, .... The algorithm is effective especially in case A and B are sparse and of large size. The Jacobi-Davidson method is used to compute a partial generalized Schur decomposition of the pair (A,B). The decomposition leads to the wanted eigenpairs.


References in zbMATH (referenced in 589 articles , 1 standard article )

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  1. Feng, Bo; Wu, Gang: On a new variant of Arnoldi method for approximation of eigenpairs (2022)
  2. Baglama, James; Bella, Tom; Picucci, Jennifer: Hybrid iterative refined method for computing a few extreme eigenpairs of a symmetric matrix (2021)
  3. Breiding, Paul; Vannieuwenhoven, Nick: The condition number of Riemannian approximation problems (2021)
  4. Chang, Wei-Chen; Li, Tiexiang; Lin, Wen-Wei; Wang, Jenn-Nan: Computation of the interior transmission eigenvalues for elastic scattering in an inhomogeneous medium containing an obstacle (2021)
  5. Huang, Jinzhi; Jia, Zhongxiao: On choices of formulations of computing the generalized singular value decomposition of a large matrix pair (2021)
  6. Huang, Tsung-Ming; Liao, Weichien; Lin, Wen-Wei; Wang, Weichung: An efficient contour integral based eigensolver for 3D dispersive photonic crystal (2021)
  7. Miao, Cun-Qiang; Wu, Wen-Ting: On relaxed filtered Krylov subspace method for non-symmetric eigenvalue problems (2021)
  8. Yue, Su-Feng; Zhang, Jian-Jun: An extended shift-invert residual Arnoldi method (2021)
  9. Ahmad, Sk. Safique; Kanhya, Prince: Structured perturbation analysis of sparse matrix pencils with (s)-specified eigenpairs (2020)
  10. Aishima, Kensuke: Convergence proof of the harmonic Ritz pairs of iterative projection methods with restart strategies for symmetric eigenvalue problems (2020)
  11. Aristodemo, A.; Gemignani, L.: Accelerating the Sinkhorn-Knopp iteration by Arnoldi-type methods (2020)
  12. Benner, Peter; Bujanović, Zvonimir; Kürschner, Patrick; Saak, Jens: A numerical comparison of different solvers for large-scale, continuous-time algebraic Riccati equations and LQR problems (2020)
  13. Blekherman, Grigoriy; Kummer, Mario; Riener, Cordian; Schweighofer, Markus; Vinzant, Cynthia: Generalized eigenvalue methods for Gaussian quadrature rules (2020)
  14. Campos, Carmen; Roman, Jose E.: A polynomial Jacobi-Davidson solver with support for non-monomial bases and deflation (2020)
  15. Carcenac, Manuel; Redif, Soydan: Application of the sequential matrix diagonalization algorithm to high-dimensional functional MRI data (2020)
  16. Dax, Achiya: A cross-product approach for low-rank approximations of large matrices (2020)
  17. Demyanko, Kirill V.; Kaporin, Igor E.; Nechepurenko, Yuri M.: Inexact Newton method for the solution of eigenproblems arising in hydrodynamic temporal stability analysis (2020)
  18. Fukaya, Takeshi; Kannan, Ramaseshan; Nakatsukasa, Yuji; Yamamoto, Yusaku; Yanagisawa, Yuka: Shifted Cholesky QR for computing the QR factorization of ill-conditioned matrices (2020)
  19. Horning, Andrew; Townsend, Alex: FEAST for differential eigenvalue problems (2020)
  20. Jia, Zhongxiao: Approximation accuracy of the Krylov subspaces for linear discrete ill-posed problems (2020)

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