subspace iteration

subspace iteration
метод итераций в подпространстве, блочно-степенной метод

Англо-русский словарь промышленной и научной лексики. 2014.

Игры ⚽ Поможем сделать НИР

Смотреть что такое "subspace iteration" в других словарях:

  • Arnoldi iteration — In numerical linear algebra, the Arnoldi iteration is an eigenvalue algorithm and an important example of iterative methods. Arnoldi finds the eigenvalues of general (possibly non Hermitian) matrices; an analogous method for Hermitian matrices is …   Wikipedia

  • Power iteration — In mathematics, the power iteration is an eigenvalue algorithm: given a matrix A , the algorithm will produce a number lambda; (the eigenvalue) and a nonzero vector v (the eigenvector), such that Av = lambda; v .The power iteration is a very… …   Wikipedia

  • Krylov subspace — In linear algebra the Krylov subspace generated by an n by n matrix, A , and an n vector, b , is the subspace mathcal{K} n spanned by the vectors of the Krylov sequence:::mathcal{K} n = operatorname{span} , { b, Ab, A^2b, ldots, A^{n 1}b }. , It… …   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

  • Derivation of the conjugate gradient method — In numerical linear algebra, the conjugate gradient method is an iterative method for numerically solving the linear system where is symmetric positive definite. The conjugate gradient method can be derived from several different perspectives,… …   Wikipedia

  • Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… …   Wikipedia

  • Gram–Schmidt process — In mathematics, particularly linear algebra and numerical analysis, the Gram–Schmidt process is a method for orthogonalizing a set of vectors in an inner product space, most commonly the Euclidean space R n . The Gram–Schmidt process takes a… …   Wikipedia

  • DIIS — (direct inversion in the iterative subspace or direct inversion of the iterative subspace), also known as Pulay mixing, is an extrapolation technique. DIIS was developed by Peter Pulay in the field of computational quantum chemistry with the… …   Wikipedia

  • Lanczos algorithm — The Lanczos algorithm is an iterative algorithm invented by Cornelius Lanczos that is an adaptation of power methods to find eigenvalues and eigenvectors of a square matrix or the singular value decomposition of a rectangular matrix. It is… …   Wikipedia

  • List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra …   Wikipedia

  • Orthogonalization — In linear algebra, orthogonalization is the process of finding a set of orthogonal vectors that span a particular subspace. Formally, starting with a linearly independent set of vectors {v1,...,vk} in an inner product space (most commonly the… …   Wikipedia


Поделиться ссылкой на выделенное

Прямая ссылка:
Нажмите правой клавишей мыши и выберите «Копировать ссылку»