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  2. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    A variant of Gaussian elimination called GaussJordan 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. Jordan matrix - Wikipedia

    en.wikipedia.org/wiki/Jordan_matrix

    Let () (that is, a n × n complex matrix) and () be the change of basis matrix to the Jordan normal form of A; that is, A = C −1 JC.Now let f (z) be a holomorphic function on an open set such that ; that is, the spectrum of the matrix is contained inside the domain of holomorphy of f.

  4. 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 GaussJordan elimination. A matrix is in column echelon form if its transpose is in

  5. Jordan normal form - Wikipedia

    en.wikipedia.org/wiki/Jordan_normal_form

    In linear algebra, a Jordan normal form, also known as a Jordan canonical form, [1] [2] is an upper triangular matrix of a particular form called a Jordan matrix representing a linear operator on a finite-dimensional vector space with respect to some basis.

  6. Frontal solver - Wikipedia

    en.wikipedia.org/wiki/Frontal_solver

    A frontal solver is an approach to solving sparse linear systems which is used extensively in finite element analysis. [1] Algorithms of this kind are variants of Gauss elimination that automatically avoids a large number of operations involving zero terms due to the fact that the matrix is only sparse. [2]

  7. System of linear equations - Wikipedia

    en.wikipedia.org/wiki/System_of_linear_equations

    Because these operations are reversible, the augmented matrix produced always represents a linear system that is equivalent to the original. There are several specific algorithms to row-reduce an augmented matrix, the simplest of which are Gaussian elimination and GaussJordan elimination. The following computation shows GaussJordan ...

  8. Jordan decomposition - Wikipedia

    en.wikipedia.org/wiki/Jordan_decomposition

    In mathematics, Jordan decomposition may refer to Hahn decomposition theorem, and the Jordan decomposition of a measure; Jordan normal form of a matrix; Jordan–Chevalley decomposition of a matrix; Deligne–Lusztig theory, and its Jordan decomposition of a character of a finite group of Lie type

  9. Schur complement - Wikipedia

    en.wikipedia.org/wiki/Schur_complement

    The Schur complement arises when performing a block Gaussian elimination on the matrix M.In order to eliminate the elements below the block diagonal, one multiplies the matrix M by a block lower triangular matrix on the right as follows: = [] [] [] = [], where I p denotes a p×p identity matrix.