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  2. Minor (linear algebra) - Wikipedia

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

    Let A be an m × n matrix and k an integer with 0 < k ≤ m, and k ≤ n.A k × k minor of A, also called minor determinant of order k of A or, if m = n, (n−k)th minor determinant of A (the word "determinant" is often omitted, and the word "degree" is sometimes used instead of "order") is the determinant of a k × k matrix obtained from A by deleting m−k rows and n−k columns.

  3. 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 ...

  4. 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 ...

  5. 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 ...

  6. Rank (linear algebra) - Wikipedia

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

    In linear algebra, the rank of a matrix A is the dimension of the vector space generated (or spanned) by its columns. [1][2][3] This corresponds to the maximal number of linearly independent columns of A. This, in turn, is identical to the dimension of the vector space spanned by its rows. [4] Rank is thus a measure of the "nondegenerateness ...

  7. Totally positive matrix - Wikipedia

    en.wikipedia.org/wiki/Totally_positive_matrix

    Totally positive matrix. In mathematics, a totally positive matrix is a square matrix in which all the minors are positive: that is, the determinant of every square submatrix is a positive number. [1] A totally positive matrix has all entries positive, so it is also a positive matrix; and it has all principal minors positive (and positive ...

  8. Kirchhoff's theorem - Wikipedia

    en.wikipedia.org/wiki/Kirchhoff's_theorem

    Kirchhoff's theorem is a generalization of Cayley's formula which provides the number of spanning trees in a complete graph. Kirchhoff's theorem relies on the notion of the Laplacian matrix of a graph, which is equal to the difference between the graph's degree matrix (the diagonal matrix of vertex degrees) and its adjacency matrix (a (0,1 ...

  9. Gershgorin circle theorem - Wikipedia

    en.wikipedia.org/wiki/Gershgorin_circle_theorem

    There are two types of continuity concerning eigenvalues: (1) each individual eigenvalue is a usual continuous function (such a representation does exist on a real interval but may not exist on a complex domain), (2) eigenvalues are continuous as a whole in the topological sense (a mapping from the matrix space with metric induced by a norm to ...