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 369 articles )

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  1. Adachi, Satoru; Iwata, Satoru; Nakatsukasa, Yuji; Takeda, Akiko: Solving the trust-region subproblem by a generalized eigenvalue problem (2017)
  2. Argentati, Merico E.; Knyazev, Andrew V.; Neymeyr, Klaus; Ovtchinnikov, Evgueni E.; Zhou, Ming: Convergence theory for preconditioned eigenvalue solvers in a nutshell (2017)
  3. Betcke, Marta M.; Voss, Heinrich: Restarting iterative projection methods for Hermitian nonlinear eigenvalue problems with minmax property (2017)
  4. Lin, Lin: Localized spectrum slicing (2017)
  5. Nakatsukasa, Yuji; Soma, Tasuku; Uschmajew, André: Finding a low-rank basis in a matrix subspace (2017)
  6. Wen, Zaiwen; Zhang, Yin: Accelerating convergence by augmented Rayleigh-Ritz projections for large-scale eigenpair computation (2017)
  7. Wu, Gang: The convergence of harmonic Ritz vectors and harmonic Ritz values, revisited (2017)
  8. Zwaan, Ian N.; Hochstenbach, Michiel E.: Krylov-Schur-type restarts for the two-sided Arnoldi method (2017)
  9. Breuer, Alex; Lumsdaine, Andrew: Matrix-free Krylov iteration for implicit convolution of numerically low-rank data (2016)
  10. Campos, Carmen; Roman, Jose E.: Restarted Q-Arnoldi-type methods exploiting symmetry in quadratic eigenvalue problems (2016)
  11. Campos, Carmen; Roman, Jose E.: Parallel Krylov solvers for the polynomial eigenvalue problem in SLEPc (2016)
  12. Chorowski, Jakub; Trabs, Mathias: Spectral estimation for diffusions with random sampling times (2016)
  13. Gaudreau, P.; Slevinsky, R.; Safouhi, H.: The double exponential sinc collocation method for singular Sturm-Liouville problems (2016)
  14. Giani, Stefano; Grubišić, Luka; Międlar, Agnieszka; Ovall, Jeffrey S.: Robust error estimates for approximations of non-self-adjoint eigenvalue problems (2016)
  15. Higham, Nicholas J.; Strabić, Nataša: Bounds for the distance to the nearest correlation matrix (2016)
  16. Huang, Tsung-Ming; Lin, Wen-Wei; Mehrmann, Volker: A Newton-type method with nonequivalence deflation for nonlinear eigenvalue problems arising in photonic crystal modeling (2016)
  17. Michaud-Rioux, Vincent; Zhang, Lei; Guo, Hong: RESCU: a real space electronic structure method (2016)
  18. Nakatsukasa, Yuji; Freund, Roland W.: Computing fundamental matrix decompositions accurately via the matrix sign function in two iterations: the power of Zolotarev’s functions (2016)
  19. Neymeyr, Klaus; Zhou, Ming: Convergence analysis of restarted Krylov subspace eigensolvers (2016)
  20. Palacios, José Luis; Quiroz, Daniel: Birth and death chains on finite trees: computing their stationary distribution and hitting times (2016)

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