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  2. Triangular matrix - Wikipedia

    en.wikipedia.org/wiki/Triangular_matrix

    In fact, a matrix A over a field containing all of the eigenvalues of A (for example, any matrix over an algebraically closed field) is similar to a triangular matrix. This can be proven by using induction on the fact that A has an eigenvector, by taking the quotient space by the eigenvector and inducting to show that A stabilizes a flag, and ...

  3. LU decomposition - Wikipedia

    en.wikipedia.org/wiki/LU_decomposition

    We define the final permutation matrix as the identity matrix which has all the same rows swapped in the same order as the matrix while it transforms into the matrix . For our matrix A ( n − 1 ) {\displaystyle A^{(n-1)}} , we may start by swapping rows to provide the desired conditions for the n-th column.

  4. Schur decomposition - Wikipedia

    en.wikipedia.org/wiki/Schur_decomposition

    In the mathematical discipline of linear algebra, the Schur decomposition or Schur triangulation, named after Issai Schur, is a matrix decomposition. It allows one to write an arbitrary complex square matrix as unitarily similar to an upper triangular matrix whose diagonal elements are the eigenvalues of the original matrix.

  5. Matrix decomposition - Wikipedia

    en.wikipedia.org/wiki/Matrix_decomposition

    Online Matrix Calculator; Wolfram Alpha Matrix Decomposition Computation » LU and QR Decomposition; Springer Encyclopaedia of Mathematics » Matrix factorization; GraphLab GraphLab collaborative filtering library, large scale parallel implementation of matrix decomposition methods (in C++) for multicore.

  6. Cholesky decomposition - Wikipedia

    en.wikipedia.org/wiki/Cholesky_decomposition

    In linear algebra, the Cholesky decomposition or Cholesky factorization (pronounced / ʃ ə ˈ l ɛ s k i / shə-LES-kee) is a decomposition of a Hermitian, positive-definite matrix into the product of a lower triangular matrix and its conjugate transpose, which is useful for efficient numerical solutions, e.g., Monte Carlo simulations.

  7. Matrix chain multiplication - Wikipedia

    en.wikipedia.org/wiki/Matrix_chain_multiplication

    For the example below, there are four sides: A, B, C and the final result ABC. A is a 10×30 matrix, B is a 30×5 matrix, C is a 5×60 matrix, and the final result is a 10×60 matrix. The regular polygon for this example is a 4-gon, i.e. a square: The matrix product AB is a 10x5 matrix and BC is a 30x60 matrix.

  8. Hessenberg matrix - Wikipedia

    en.wikipedia.org/wiki/Hessenberg_matrix

    A square matrix is said to be in lower Hessenberg form or to be a lower Hessenberg matrix if its transpose is an upper Hessenberg matrix or equivalently if , = for all , with > +. A lower Hessenberg matrix is called unreduced if all superdiagonal entries are nonzero, i.e. if a i , i + 1 ≠ 0 {\displaystyle a_{i,i+1}\neq 0} for all i ∈ { 1 ...

  9. Crout matrix decomposition - Wikipedia

    en.wikipedia.org/wiki/Crout_matrix_decomposition

    In linear algebra, the Crout matrix decomposition is an LU decomposition which decomposes a matrix into a lower triangular matrix (L), an upper triangular matrix (U) and, although not always needed, a permutation matrix (P). It was developed by Prescott Durand Crout. [1] The Crout matrix decomposition algorithm differs slightly from the ...