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  2. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    A variant of Gaussian elimination called Gauss–Jordan elimination can be used for finding the inverse of a matrix, if it exists. If A is an n × n square matrix, then one can use row reduction to compute its inverse matrix, if it exists. First, the n × n identity matrix is augmented to the right of A, forming an n × 2n block matrix [A | I].

  3. Pivot element - Wikipedia

    en.wikipedia.org/wiki/Pivot_element

    The pivot or pivot element is the element of a matrix, or an array, which is selected first by an algorithm (e.g. Gaussian elimination, simplex algorithm, etc.), to do certain calculations. In the case of matrix algorithms, a pivot entry is usually required to be at least distinct from zero, and often distant from it; in this case finding this ...

  4. LU decomposition - Wikipedia

    en.wikipedia.org/wiki/LU_decomposition

    Before Gauss many mathematicians in Eurasia were performing and perfecting it yet as the method became relegated to school grade, few of them left any detailed descriptions. Thus the name Gaussian elimination is only a convenient abbreviation of a complex history. The Polish astronomer Tadeusz Banachiewicz introduced the LU decomposition in ...

  5. Row echelon form - Wikipedia

    en.wikipedia.org/wiki/Row_echelon_form

    The reduced row echelon form of a matrix is unique and does not depend on the sequence of elementary row operations used to obtain it. The variant of Gaussian elimination that transforms a matrix to reduced row echelon form is sometimes called Gauss–Jordan elimination. A matrix is in column echelon form if its transpose is in row echelon form.

  6. QR decomposition - Wikipedia

    en.wikipedia.org/wiki/QR_decomposition

    Column pivoting is useful when A is ... by Gaussian elimination or compute ... Online Matrix Calculator Performs QR decomposition of matrices.

  7. Tridiagonal matrix algorithm - Wikipedia

    en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm

    In numerical linear algebra, the tridiagonal matrix algorithm, also known as the Thomas algorithm (named after Llewellyn Thomas), is a simplified form of Gaussian elimination that can be used to solve tridiagonal systems of equations. A tridiagonal system for n unknowns may be written as

  8. Diagonally dominant matrix - Wikipedia

    en.wikipedia.org/wiki/Diagonally_dominant_matrix

    No (partial) pivoting is necessary for a strictly column diagonally dominant matrix when performing Gaussian elimination (LU factorization). The Jacobi and Gauss–Seidel methods for solving a linear system converge if the matrix is strictly (or irreducibly) diagonally dominant. Many matrices that arise in finite element methods are diagonally ...

  9. Cauchy matrix - Wikipedia

    en.wikipedia.org/wiki/Cauchy_matrix

    "Fast Gaussian elimination with partial pivoting for matrices with displacement structure" (PDF). Mathematics of Computation. 64 (212): 1557 ...