- generalized eigenvalue
- мат. обобщенное собственное значение
Большой англо-русский и русско-английский словарь. 2001.
generalized eigenvalue
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Eigenvalue perturbation — is a perturbation approach to finding eigenvalues and eigenvectors of systems perturbed from one with known eigenvectors and eigenvalues. It also allows one to determine the sensitivity of the eigenvalues and eigenvectors with respect to changes… … Wikipedia
Eigenvalue algorithm — In linear algebra, one of the most important problems is designing efficient and stable algorithms for finding the eigenvalues of a matrix. These eigenvalue algorithms may also find eigenvectors. Contents 1 Characteristic polynomial 2 Power… … Wikipedia
Eigenvalue, eigenvector and eigenspace — In mathematics, given a linear transformation, an Audio|De eigenvector.ogg|eigenvector of that linear transformation is a nonzero vector which, when that transformation is applied to it, changes in length, but not direction. For each eigenvector… … Wikipedia
Generalized eigenvector — In linear algebra, a generalized eigenvector of a matrix A is a nonzero vector v, which has associated with it an eigenvalue lambda; having algebraic multiplicity k ge;1, satisfying: (A lambda I)^kmathbf{v} = mathbf{0}.Ordinary eigenvectors are… … Wikipedia
Generalized minimal residual method — In mathematics, the generalized minimal residual method (usually abbreviated GMRES) is an iterative method for the numerical solution of a system of linear equations. The method approximates the solution by the vector in a Krylov subspace with… … Wikipedia
Quadratic eigenvalue problem — In mathematics, the quadratic eigenvalue problem [F. Tisseur and K. Meerbergen, The quadratic eigenvalue problem, SIAMRev., 43 (2001), pp. 235–286.] (QEP) , is to find scalar eigenvalues lambda,, left eigenvectors y, and right eigenvectors x,… … Wikipedia
Cheng's eigenvalue comparison theorem — In Riemannian geometry, Cheng s eigenvalue comparison theorem states in general terms that when a domain is large, the first Dirichlet eigenvalue of its Laplace–Beltrami operator is small. This general characterization is not precise, in part… … Wikipedia
Jacobi eigenvalue algorithm — The Jacobi eigenvalue algorithm is a numerical procedure for the calculation of all eigenvalues and eigenvectors of a real symmetric matrix. Description Let varphi in mathbb{R}, , 1 le k < l le n and let J(varphi, k, l) denote the n imes n matrix … Wikipedia
Eigenvalues and eigenvectors — For more specific information regarding the eigenvalues and eigenvectors of matrices, see Eigendecomposition of a matrix. In this shear mapping the red arrow changes direction but the blue arrow does not. Therefore the blue arrow is an… … Wikipedia
Eigendecomposition of a matrix — In the mathematical discipline of linear algebra, eigendecomposition or sometimes spectral decomposition is the factorization of a matrix into a canonical form, whereby the matrix is represented in terms of its eigenvalues and… … Wikipedia
Schur decomposition — In the mathematical discipline of linear algebra, the Schur decomposition or Schur triangulation (named after Issai Schur) is an important matrix decomposition. Statement The Schur decomposition reads as follows: if A is a n times; n square… … Wikipedia
