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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. 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 row echelon form.

  4. Jordan normal form - Wikipedia

    en.wikipedia.org/wiki/Jordan_normal_form

    This real Jordan form is a consequence of the complex Jordan form. For a real matrix the nonreal eigenvectors and generalized eigenvectors can always be chosen to form complex conjugate pairs. Taking the real and imaginary part (linear combination of the vector and its conjugate), the matrix has this form with respect to the new basis.

  5. LU decomposition - Wikipedia

    en.wikipedia.org/wiki/LU_decomposition

    To quote: "It appears that Gauss and Doolittle applied the method [of elimination] only to symmetric equations. More recent authors, for example, Aitken, Banachiewicz, Dwyer, and Crout … have emphasized the use of the method, or variations of it, in connection with non-symmetric problems …

  6. 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.

  7. Discrete ordinates method - Wikipedia

    en.wikipedia.org/wiki/Discrete_Ordinates_Method

    It is possible to solve the resulting linear system directly with GaussJordan elimination, [2] but this is problematic due to the large memory requirement for storing the matrix of the linear system. Another way is to use iterative methods, where the required number of iterations for a given degree of accuracy depends on the strength of ...

  8. Talk:Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Talk:Gaussian_elimination

    "The Gauss-Jordan (GJ) method is a variant of Gaussian elimination (GE). It differs in eliminating the unknown equations above the main diagonal as well as below the main diagonal. The Gauss-Jordan method is equivalent to the use of reduced row echelon form of linear algebra texts. GJ requires 50% more multiplication and division operation than ...

  9. Gauss–Seidel method - Wikipedia

    en.wikipedia.org/wiki/Gauss–Seidel_method

    In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a system of linear equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel .