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 410 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. Aishima, Kensuke: On convergence of iterative projection methods for symmetric eigenvalue problems (2017)
  3. Antoine, Xavier; Levitt, Antoine; Tang, Qinglin: Efficient spectral computation of the stationary states of rotating Bose-Einstein condensates by preconditioned nonlinear conjugate gradient methods (2017)
  4. Argentati, Merico E.; Knyazev, Andrew V.; Neymeyr, Klaus; Ovtchinnikov, Evgueni E.; Zhou, Ming: Convergence theory for preconditioned eigenvalue solvers in a nutshell (2017)
  5. Betcke, Marta M.; Voss, Heinrich: Restarting iterative projection methods for Hermitian nonlinear eigenvalue problems with minmax property (2017)
  6. Lin, Lin: Localized spectrum slicing (2017)
  7. Nakatsukasa, Yuji: Accuracy of singular vectors obtained by projection-based SVD methods (2017)
  8. Nakatsukasa, Yuji; Soma, Tasuku; Uschmajew, André: Finding a low-rank basis in a matrix subspace (2017)
  9. Pequito, Sérgio; Ramos, Guilherme; Kar, Soummya; Aguiar, A.Pedro; Ramos, Jaime: The robust minimal controllability problem (2017)
  10. Wang, Wei-Guo; Wei, Yimin: Mixed and componentwise condition numbers for matrix decompositions (2017)
  11. Wang, Xiang; Tang, Xiao-Bin; Mao, Liang-Zhi: A modified second-order Arnoldi method for solving the quadratic eigenvalue problems (2017)
  12. Wen, Zaiwen; Zhang, Yin: Accelerating convergence by augmented Rayleigh-Ritz projections for large-scale eigenpair computation (2017)
  13. Wu, Gang: The convergence of harmonic Ritz vectors and harmonic Ritz values, revisited (2017)
  14. Wu, Gang; Pang, Hong-Kui: On the correction equation of the Jacobi-Davidson method (2017)
  15. Zwaan, Ian N.; Hochstenbach, Michiel E.: Krylov-Schur-type restarts for the two-sided Arnoldi method (2017)
  16. Bangay, Shaun; Beliakov, Gleb: On the fast Lanczos method for computation of eigenvalues of Hankel matrices using multiprecision arithmetics. (2016)
  17. Breuer, Alex; Lumsdaine, Andrew: Matrix-free Krylov iteration for implicit convolution of numerically low-rank data (2016)
  18. Campos, Carmen; Roman, Jose E.: Restarted Q-Arnoldi-type methods exploiting symmetry in quadratic eigenvalue problems (2016)
  19. Campos, Carmen; Roman, Jose E.: Parallel Krylov solvers for the polynomial eigenvalue problem in SLEPc (2016)
  20. Chorowski, Jakub; Trabs, Mathias: Spectral estimation for diffusions with random sampling times (2016)

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