diagonal decomposition
1Decomposition en valeurs singulieres — Décomposition en valeurs singulières En mathématiques, le procédé d algèbre linéaire de décomposition en valeurs singulières (ou SVD, de l anglais : Singular Value Decomposition) d une matrice est un outil important de factorisation des… …
2Décomposition En Valeurs Singulières — En mathématiques, le procédé d algèbre linéaire de décomposition en valeurs singulières (ou SVD, de l anglais : Singular Value Decomposition) d une matrice est un outil important de factorisation des matrices rectangulaires réelles ou… …
3Décomposition en valeurs singulières — En mathématiques, le procédé d algèbre linéaire de décomposition en valeurs singulières (ou SVD, de l anglais : Singular Value Decomposition) d une matrice est un outil important de factorisation des matrices rectangulaires réelles ou… …
4Diagonal matrix — In linear algebra, a diagonal matrix is a matrix (usually a square matrix) in which the entries outside the main diagonal (↘) are all zero. The diagonal entries themselves may or may not be zero. Thus, the matrix D = (di,j) with n columns and n… …
5Matrix decomposition — In the mathematical discipline of linear algebra, a matrix decomposition is a factorization of a matrix into some canonical form. There are many different matrix decompositions; each finds use among a particular class of problems. Contents 1… …
6Singular value decomposition — Visualization of the SVD of a 2 dimensional, real shearing matrix M. First, we see the unit disc in blue together with the two canonical unit vectors. We then see the action of M, which distorts the disk to an ellipse. The SVD decomposes M into… …
7LU decomposition — In linear algebra, LU decomposition (also called LU factorization) is a matrix decomposition which writes a matrix as the product of a lower triangular matrix and an upper triangular matrix. The product sometimes includes a permutation matrix as… …
8Cholesky decomposition — In linear algebra, the Cholesky decomposition or Cholesky triangle is a decomposition of a Hermitian, positive definite matrix into the product of a lower triangular matrix and its conjugate transpose. It was discovered by André Louis Cholesky… …
9Schur 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… …
10Schmidt decomposition — In linear algebra, the Schmidt decomposition refers to a particular way of expressing a vector in the tensor product of two inner product spaces. It has applications in quantum information theory and plasticity. Theorem Let H 1 and H 2 be Hilbert …
