Nachschlagewerk MQL5Matrizen und VektorenOpenBLASEigen ValuesSymmetric Matrices

Symmetric Matrices

Functions for computing eigenvalues and eigenvectors of symmetric or Hermitian matrices using the divide and conquer algorithm, making the process efficient and fast. These methods can be applied to matrices of different data types, including real and complex numbers.

Function	Action
EigenSymmetricDC	Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugate) matrix using the divide-and-conquer algorithm (lapack functions SYEVD, HEEVD).
EigenSymmetricQR	Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugate) matrix using the QR algorithm (lapack functions SYEV, HEEV).
EigenSymmetricRobust	Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugate) matrix using the Multiple Relatively Robust Representations, MRRR algorithm (lapack functions SYEVR, HEEVR).
EigenSymmetricBisect	Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugate) matrix using the bisection algorithm (lapack functions SYEVX, HEEVX).
EigenSymmetricDC2s	Compute all eigenvalues and, optionally, eigenvectors of a real symmetric or Hermitian (complex conjugated) matrix using the 2stage technique for the reduction to tridiagonal. If eigenvectors are desired, it uses a divide and conquer algorithm (lapack functions SYEVD_2STAGE, HEEVD_2STAGE).
EigenSymmetricQR2s	Compute all eigenvalues and, optionally, eigenvectors of a real symmetric or Hermitian (complex conjugated) matrix using the 2stage technique for the reduction to tridiagonal (lapack functions SYEV_2STAGE, HEEV_2STAGE).
EigenSymmetricRobust2s	Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugated) matrix using the 2stage technique for the reduction to tridiagonal then using the Multiple Relatively Robust Representations, MRRR algorithm (lapack functions SYEVR_2STAGE, HEEVR_2STAGE).
EigenSymmetricBisect2s	Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugated) matrix using the 2stage technique for the reduction to tridiagonal then using the bisection algorithm (lapack functions SYEVX_2STAGE, HEEVX_2STAGE).
EigenSymmetric2DC	Compute all the eigenvalues, and optionally, the eigenvectors of a generalized symmetric-definite eigenproblem, of the form Ax=(lambda)Bx, ABx=(lambda)x, or BAx=(lambda)x.
EigenSymmetric2QR	Compute all the eigenvalues, and optionally, the eigenvectors of a generalized symmetric-definite eigenproblem, of the form Ax=(lambda)Bx, ABx=(lambda)x, or BAx=(lambda)x.
EigenSymmetric2Bisect	Compute all the eigenvalues, and optionally, the eigenvectors of a generalized symmetric-definite eigenproblem, of the form Ax=(lambda)Bx, ABx=(lambda)x, or BAx=(lambda)x.

EigenSolver2ShurBlocked

EigenSymmetricDC