- Referenced in 88 articles
- methods are based on matrix eigenvalue decompositions...
- Referenced in 196 articles
- SLEPc the Scalable Library for Eigenvalue Problem Computations, is a software library for the solution ... such as the singular value decomposition or the quadratic eigenvalue problem...
- Referenced in 600 articles
- used for computing a few selected eigenvalues with some desirable property together with the associated ... used to compute a partial generalized Schur decomposition of the pair (A,B). The decomposition...
- Referenced in 37 articles
- assumptions regarding the component variance matrix eigenvalue decomposition. Moreover, different information criteria for choosing...
- Referenced in 488 articles
- collection of Fortran subroutines that compute the eigenvalues and eigenvectors of nine classes of matrices ... routines are included that use singular value decomposition to solve certain least-squares problems. EISPACK...
- Referenced in 504 articles
- used for computing a few selected eigenvalues with some desirable property together with the associated ... used to compute a partial Schur decomposition of A. The decomposition leads to the wanted...
- Referenced in 71 articles
- unconstrained minimization, to compute eigenvalues, eigenvectors, the singular value decomposition, or the QR decomposition...
- Referenced in 10 articles
- Cholesky, QR, and symmetric eigenvalue decomposition are implemented in AlgoPy. We discuss the reasons...
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- other key numerical component is eigenvalue decomposition for symmetric matrices, achieved by Matlab’s built...
- Referenced in 48 articles
- about the eigenvalues of the system to be defined, and no spectral decomposition...
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- standard approaches to the solution of matrix eigenvalue problems fail due to the exponentially growing ... Tucker decomposition to develop a low-rank variant of LOBPCG, a classical preconditioned eigenvalue solver ... adapted to the hierarchical Tucker decomposition. Finally, a combination of ALS and MALS with LOBPCG...
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- Cholesky decomposition, QR triangularisation, singular value decomposition, eigenvalues of a symmetric matrix, sorting, fast Fourier...
- Referenced in 16 articles
- article describes Fortran 77 subroutines for computing eigenvalues and invariant subspaces of Hamiltonian and skew ... decompositions, implying numerical backward stability as well as symmetry preservation for the computed eigenvalues. These ... efficient implementation for computing symplectic QR decompositions is provided. We demonstrate the usefulness...
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- algorithm, respectively. Only the one-step eigenvalue decomposition (EVD) is needed to estimate delay...
- Referenced in 19 articles
- decomposition of H without explicitly forming the elements of H. If only the eigenvalues...
- Referenced in 35 articles
- eigenvector. The problem arises in the decomposition of a covariance matrix into sparse factors ... classical variational representation of the largest eigenvalue of a symmetric matrix, where cardinality is constrained...
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- other related decompositions (generalized eigenvalue decomposition, generalized partial least squares-singular value decomposition). Furthermore, GSVD...
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- square matrix), using a model-based eigenvalue decomposition and regression. Missing data is accommodated...
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- Schur decomposition of a complex Hessenberg matrix. Together with existing ScaLAPACK routines, the eigenvalues ... parallel $QR$ algorithm.This parallel complex Schur decomposition routine was developed to fill a void...
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- solving the stiffness matrix by the eigenvalue decomposition are present. Moreover, we also develop...