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  2. Diagonally dominant matrix - Wikipedia

    en.wikipedia.org/wiki/Diagonally_dominant_matrix

    A strictly diagonally dominant matrix (or an irreducibly diagonally dominant matrix [2]) is non-singular. A Hermitian diagonally dominant matrix with real non-negative diagonal entries is positive semidefinite. This follows from the eigenvalues being real, and Gershgorin's circle theorem. If the symmetry requirement is eliminated, such a matrix ...

  3. Jacobi method - Wikipedia

    en.wikipedia.org/wiki/Jacobi_method

    The standard convergence condition (for any iterative method) is when the spectral radius of the iteration matrix is less than 1: ((+)) < A sufficient (but not necessary) condition for the method to converge is that the matrix A is strictly or irreducibly diagonally dominant. Strict row diagonal dominance means that for each row, the absolute ...

  4. Gauss–Seidel method - Wikipedia

    en.wikipedia.org/wiki/Gauss–Seidel_method

    Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either strictly diagonally dominant, [1] or symmetric and positive definite. It was only mentioned in a private letter from Gauss to his student Gerling in 1823. [2] A publication was not delivered before 1874 by ...

  5. Dominator (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Dominator_(graph_theory)

    The dominance frontier of a node d is the set of all nodes n i such that d dominates an immediate predecessor of n i, but d does not strictly dominate n i. It is the set of nodes where d 's dominance stops. A dominator tree is a tree where each node's children are those nodes it immediately dominates. The start node is the root of the tree.

  6. Power iteration - Wikipedia

    en.wikipedia.org/wiki/Power_iteration

    Since generically, the dominant eigenvalue of is unique, the first Jordan block of is the matrix [], where is the largest eigenvalue of A in magnitude. The starting vector b 0 {\displaystyle b_{0}} can be written as a linear combination of the columns of V :

  7. Perron–Frobenius theorem - Wikipedia

    en.wikipedia.org/wiki/Perron–Frobenius_theorem

    Let = be an positive matrix: > for ,.Then the following statements hold. There is a positive real number r, called the Perron root or the Perron–Frobenius eigenvalue (also called the leading eigenvalue, principal eigenvalue or dominant eigenvalue), such that r is an eigenvalue of A and any other eigenvalue λ (possibly complex) in absolute value is strictly smaller than r, |λ| < r.

  8. Weakly chained diagonally dominant matrix - Wikipedia

    en.wikipedia.org/wiki/Weakly_chained_diagonally...

    A complex square matrix is said to be weakly chained diagonally dominant (WCDD) if A {\displaystyle A} is WDD and for each row i 1 {\displaystyle i_{1}} that is not SDD, there exists a walk i 1 → i 2 → ⋯ → i k {\displaystyle i_{1}\rightarrow i_{2}\rightarrow \cdots \rightarrow i_{k}} in the directed graph of A {\displaystyle A} ending ...

  9. Tridiagonal matrix algorithm - Wikipedia

    en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm

    In numerical linear algebra, the tridiagonal matrix algorithm, also known as the Thomas algorithm (named after Llewellyn Thomas), is a simplified form of Gaussian elimination that can be used to solve tridiagonal systems of equations. A tridiagonal system for n unknowns may be written as