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 542 articles , 1 standard article )

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  1. Dax, Achiya: A cross-product approach for low-rank approximations of large matrices (2020)
  2. Fukaya, Takeshi; Kannan, Ramaseshan; Nakatsukasa, Yuji; Yamamoto, Yusaku; Yanagisawa, Yuka: Shifted Cholesky QR for computing the QR factorization of ill-conditioned matrices (2020)
  3. Rong, Xin; Niu, Ruiping; Liu, Guirong: Stability analysis of smoothed finite element methods with explicit method for transient heat transfer problems (2020)
  4. Adachi, Satoru; Nakatsukasa, Yuji: Eigenvalue-based algorithm and analysis for nonconvex QCQP with one constraint (2019)
  5. Altmann, R.; Peterseim, D.: Localized computation of eigenstates of random Schrödinger operators (2019)
  6. Bai, Zhong-Zhi; Miao, Cun-Qiang: Computing eigenpairs of Hermitian matrices in perfect Krylov subspaces (2019)
  7. Chen, Xiao Shan; Vong, Seak-Weng; Li, Wen; Xu, Hongguo: Noda iterations for generalized eigenproblems following Perron-Frobenius theory (2019)
  8. Goldenberg, Steven; Stathopoulos, Andreas; Romero, Eloy: A Golub-Kahan Davidson method for accurately computing a few singular triplets of large sparse matrices (2019)
  9. Hochstenbach, Michiel E.; Mehl, Christian; Plestenjak, Bor: Solving singular generalized eigenvalue problems by a rank-completing perturbation (2019)
  10. Huang, Ruihao; Mu, Lin: A new fast method of solving the high dimensional elliptic eigenvalue problem (2019)
  11. Huang, Wei-Qiang; Lin, Wen-Wei; Lu, Henry Horng-Shing; Yau, Shing-Tung: iSIRA: integrated shift-invert residual Arnoldi method for graph Laplacian matrices from big data (2019)
  12. Huhtanen, Marko; Kotila, Vesa: Optimal quotients for solving large eigenvalue problems (2019)
  13. Ismail, M. E. H.; Ranga, A. Sri: (R_II) type recurrence, generalized eigenvalue problem and orthogonal polynomials on the unit circle (2019)
  14. Kim, Yunho: An unconstrained global optimization framework for real symmetric eigenvalue problems (2019)
  15. Liu, J.; Sun, J.; Turner, T.: Spectral indicator method for a non-selfadjoint Steklov eigenvalue problem (2019)
  16. Maday, Yvon; Marcati, Carlo: Regularity and (hp) discontinuous Galerkin finite element approximation of linear elliptic eigenvalue problems with singular potentials (2019)
  17. Miao, Cun-Qiang; Liu, Hao: Rayleigh quotient minimization method for symmetric eigenvalue problems (2019)
  18. Pandur, Marija Miloloža: Preconditioned gradient iterations for the eigenproblem of definite matrix pairs (2019)
  19. Portal, Alberto; Zufiria, Pedro J.: On the minimum number of general or dedicated controllers required for system controllability (2019)
  20. Yin, Guojian: A harmonic FEAST algorithm for non-Hermitian generalized eigenvalue problems (2019)

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