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  2. Cramer's rule - Wikipedia

    en.wikipedia.org/wiki/Cramer's_rule

    3 Finding inverse matrix. 4 Applications. ... Cramer's rule is an explicit formula for the solution of a system of linear equations with as many equations as unknowns

  3. Invertible matrix - Wikipedia

    en.wikipedia.org/wiki/Invertible_matrix

    The conditions for existence of left-inverse or right-inverse are more complicated, since a notion of rank does not exist over rings. The set of n × n invertible matrices together with the operation of matrix multiplication and entries from ring R form a group, the general linear group of degree n, denoted GL n (R).

  4. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    Cramer's rule is a closed-form expression, in terms of determinants, of the solution of a system of n linear equations in n unknowns. Cramer's rule is useful for reasoning about the solution, but, except for n = 2 or 3 , it is rarely used for computing a solution, since Gaussian elimination is a faster algorithm.

  5. Unimodular matrix - Wikipedia

    en.wikipedia.org/wiki/Unimodular_matrix

    Equivalently, it is an integer matrix that is invertible over the integers: there is an integer matrix N that is its inverse (these are equivalent under Cramer's rule). Thus every equation Mx = b, where M and b both have integer components and M is unimodular, has an integer solution.

  6. 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]

  7. System of linear equations - Wikipedia

    en.wikipedia.org/wiki/System_of_linear_equations

    Cramer's rule is an explicit formula for the solution of a system of linear ... all solutions (if any exist) are given using the Moore–Penrose inverse of A, ...

  8. Adjugate matrix - Wikipedia

    en.wikipedia.org/wiki/Adjugate_matrix

    In linear algebra, the adjugate or classical adjoint of a square matrix A, adj(A), is the transpose of its cofactor matrix. [1] [2] It is occasionally known as adjunct matrix, [3] [4] or "adjoint", [5] though that normally refers to a different concept, the adjoint operator which for a matrix is the conjugate transpose.

  9. Nakayama's lemma - Wikipedia

    en.wikipedia.org/wiki/Nakayama's_lemma

    2.5 Inverse function theorem. 3 Proof. ... The required result follows by multiplying by the adjugate of the matrix (φδ ij − a ij) and invoking Cramer's rule.