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  2. Minor (linear algebra) - Wikipedia

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

    In linear algebra, a minor of a matrix A is the determinant of some smaller square matrix, cut down from A by removing one or more of its rows and columns. Minors obtained by removing just one row and one column from square matrices (first minors) are required for calculating matrix cofactors, which in turn are useful for computing both the determinant and inverse of square matrices.

  3. Laplace expansion - Wikipedia

    en.wikipedia.org/wiki/Laplace_expansion

    Laplace expansion. In linear algebra, the Laplace expansion, named after Pierre-Simon Laplace, also called cofactor expansion, is an expression of the determinant of an n × n - matrix B as a weighted sum of minors, which are the determinants of some (n − 1) × (n − 1) - submatrices of B. Specifically, for every i, the Laplace expansion ...

  4. Cramer's rule - Wikipedia

    en.wikipedia.org/wiki/Cramer's_rule

    Cramer's rule. In linear algebra, Cramer's rule is an explicit formula for the solution of a system of linear equations with as many equations as unknowns, valid whenever the system has a unique solution. It expresses the solution in terms of the determinants of the (square) coefficient matrix and of matrices obtained from it by replacing one ...

  5. Determinant - Wikipedia

    en.wikipedia.org/wiki/Determinant

    Determinant. In mathematics, the determinant is a scalar -valued function of the entries of a square matrix. The determinant of a matrix A is commonly denoted det (A), det A, or |A|. Its value characterizes some properties of the matrix and the linear map represented, on a given basis, by the matrix. In particular, the determinant is nonzero if ...

  6. Rank (linear algebra) - Wikipedia

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

    A non-vanishing p-minor (p × p submatrix with non-zero determinant) shows that the rows and columns of that submatrix are linearly independent, and thus those rows and columns of the full matrix are linearly independent (in the full matrix), so the row and column rank are at least as large as the determinantal rank; however, the converse is ...

  7. Sylvester's criterion - Wikipedia

    en.wikipedia.org/wiki/Sylvester's_criterion

    Sylvester's criterion states that a n × n Hermitian matrix M is positive-definite if and only if all the following matrices have a positive determinant: M itself. In other words, all of the leading principal minors must be positive. By using appropriate permutations of rows and columns of M, it can also be shown that the positivity of any ...

  8. Compound matrix - Wikipedia

    en.wikipedia.org/wiki/Compound_matrix

    In linear algebra, a branch of mathematics, a (multiplicative) compound matrix is a matrix whose entries are all minors, of a given size, of another matrix. [1][2][3][4] Compound matrices are closely related to exterior algebras, [5] and their computation appears in a wide array of problems, such as in the analysis of nonlinear time-varying ...

  9. LU decomposition - Wikipedia

    en.wikipedia.org/wiki/LU_decomposition

    LU decomposition can be viewed as the matrix form of Gaussian elimination. Computers usually solve square systems of linear equations using LU decomposition, and it is also a key step when inverting a matrix or computing the determinant of a matrix. The LU decomposition was introduced by the Polish astronomer Tadeusz Banachiewicz in 1938. [1]