JDQR

From this page you can get a Matlab® implementation of the JDQR algorithm. The JDQR algorithm can be used for computing a few selected eigenvalues with some desirable property together with the associated eigenvectors of a matrix A. The matrix can be real or complex, Hermitian or non-Hermitian, .... The algorithm is effective especially in case A is sparse and of large size. The Jacobi-Davidson method is used to compute a partial Schur decomposition of A. The decomposition leads to the wanted eigenpairs.


References in zbMATH (referenced in 504 articles )

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  1. Cavaliere, F.; Zlotnik, S.; Sevilla, R.; Larrayoz, X.; Díez, P.: Nonintrusive parametric solutions in structural dynamics (2022)
  2. Feng, Bo; Wu, Gang: On a new variant of Arnoldi method for approximation of eigenpairs (2022)
  3. Lampe, Jörg; Voss, Heinrich: A survey on variational characterizations for nonlinear eigenvalue problems (2022)
  4. Nedzhibov, Gyurhan H.: The Weierstrass iterative method as a Petrov-Galerkin method for solving eigenvalue problem (2022)
  5. Petkov, Petko H.; Konstantinov, Mihail M.: The numerical Jordan form (2022)
  6. Rontsis, Nikitas; Goulart, Paul; Nakatsukasa, Yuji: Efficient semidefinite programming with approximate ADMM (2022)
  7. Tropp, Joel A.: Randomized block Krylov methods for approximating extreme eigenvalues (2022)
  8. Baglama, James; Bella, Tom; Picucci, Jennifer: Hybrid iterative refined method for computing a few extreme eigenpairs of a symmetric matrix (2021)
  9. Baglama, James; Bella, Tom; Picucci, Jennifer: Hybrid iterative refined method for computing a few extreme eigenpairs of a symmetric matrix (2021)
  10. Breiding, Paul; Vannieuwenhoven, Nick: The condition number of Riemannian approximation problems (2021)
  11. Huang, Jinzhi; Jia, Zhongxiao: On choices of formulations of computing the generalized singular value decomposition of a large matrix pair (2021)
  12. Huang, Rong: Accurate computation of generalized eigenvalues of regular SR-BP pairs (2021)
  13. Li, Quhao; Sigmund, Ole; Jensen, Jakob Søndergaard; Aage, Niels: Reduced-order methods for dynamic problems in topology optimization: a comparative study (2021)
  14. Aishima, Kensuke: Convergence proof of the harmonic Ritz pairs of iterative projection methods with restart strategies for symmetric eigenvalue problems (2020)
  15. Aristodemo, A.; Gemignani, L.: Accelerating the Sinkhorn-Knopp iteration by Arnoldi-type methods (2020)
  16. 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)
  17. Blekherman, Grigoriy; Kummer, Mario; Riener, Cordian; Schweighofer, Markus; Vinzant, Cynthia: Generalized eigenvalue methods for Gaussian quadrature rules (2020)
  18. Campos, Carmen; Roman, Jose E.: A polynomial Jacobi-Davidson solver with support for non-monomial bases and deflation (2020)
  19. Carcenac, Manuel; Redif, Soydan: Application of the sequential matrix diagonalization algorithm to high-dimensional functional MRI data (2020)
  20. Dax, Achiya: A cross-product approach for low-rank approximations of large matrices (2020)

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