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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. Row echelon form - Wikipedia

    en.wikipedia.org/wiki/Row_echelon_form

    A matrix is in reduced row echelon form if it is in row echelon form, with the additional property that the first nonzero entry of each row is equal to and is the only nonzero entry of its column. 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.

  4. Kron reduction - Wikipedia

    en.wikipedia.org/wiki/Kron_reduction

    Select the Kth row/column used to model the undesired internal nodes to be eliminated. Apply the below formula to all other matrix entries that do not reside on the Kth row and column. Then simply remove the Kth row and column of the matrix, which reduces the size of the matrix by one. Kron Reduction for the Kth row/column of an NxN matrix:

  5. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The row space is defined similarly. The row space and the column space of a matrix A are sometimes denoted as C(A T) and C(A) respectively. [2] This article considers matrices of real numbers. The row and column spaces are subspaces of the real spaces and respectively. [3]

  6. Reduction (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Reduction_(mathematics)

    In linear algebra, reduction refers to applying simple rules to a series of equations or matrices to change them into a simpler form. In the case of matrices, the process involves manipulating either the rows or the columns of the matrix and so is usually referred to as row-reduction or column-reduction, respectively.

  7. Rank (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Rank_(linear_algebra)

    Once in row echelon form, the rank is clearly the same for both row rank and column rank, and equals the number of pivots (or basic columns) and also the number of non-zero rows. For example, the matrix A given by = [] can be put in reduced row-echelon form by using the following elementary row operations: [] + [] + [] + [] + [] . The final ...

  8. Matrix (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Matrix_(mathematics)

    A matrix with the same number of rows and columns is called a square matrix. [5] A matrix with an infinite number of rows or columns (or both) is called an infinite matrix. In some contexts, such as computer algebra programs, it is useful to consider a matrix with no rows or no columns, called an empty matrix.

  9. Pivot element - Wikipedia

    en.wikipedia.org/wiki/Pivot_element

    A pivot position in a matrix, A, is a position in the matrix that corresponds to a row–leading 1 in the reduced row echelon form of A. Since the reduced row echelon form of A is unique, the pivot positions are uniquely determined and do not depend on whether or not row interchanges are performed in the reduction process. Also, the pivot of a ...