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  2. Condition number - Wikipedia

    en.wikipedia.org/wiki/Condition_number

    The condition number is derived from the theory of propagation of uncertainty, and is formally defined as the value of the asymptotic worst-case relative change in output for a relative change in input. The "function" is the solution of a problem and the "arguments" are the data in the problem. The condition number is frequently applied to ...

  3. Preconditioner - Wikipedia

    en.wikipedia.org/wiki/Preconditioner

    Preconditioner. In mathematics, preconditioning is the application of a transformation, called the preconditioner, that conditions a given problem into a form that is more suitable for numerical solving methods. Preconditioning is typically related to reducing a condition number of the problem.

  4. Circulant matrix - Wikipedia

    en.wikipedia.org/wiki/Circulant_matrix

    Circulant matrix. In linear algebra, a circulant matrix is a square matrix in which all rows are composed of the same elements and each row is rotated one element to the right relative to the preceding row. It is a particular kind of Toeplitz matrix. In numerical analysis, circulant matrices are important because they are diagonalized by a ...

  5. Jacobi eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Jacobi_eigenvalue_algorithm

    In case of a symmetric matrix it is the largest absolute value of its eigenvectors and thus equal to its spectral radius. Condition number The condition number of a nonsingular matrix is defined as = ‖ ‖ ‖ ‖. In case of a symmetric matrix it is the absolute value of the quotient of the largest and smallest eigenvalue.

  6. Moore–Penrose inverse - Wikipedia

    en.wikipedia.org/wiki/Moore–Penrose_inverse

    In mathematics, and in particular linear algebra, the Moore–Penrose inverse⁠ ⁠ of a matrix ⁠ ⁠, often called the pseudoinverse, is the most widely known generalization of the inverse matrix. [ 1 ] It was independently described by E. H. Moore in 1920, [ 2 ] Arne Bjerhammar in 1951, [ 3 ] and Roger Penrose in 1955. [ 4 ]

  7. Hilbert matrix - Wikipedia

    en.wikipedia.org/wiki/Hilbert_matrix

    In linear algebra, a Hilbert matrix, introduced by Hilbert (1894), is a square matrix with entries being the unit fractions. For example, this is the 5 × 5 Hilbert matrix: The entries can also be defined by the integral. that is, as a Gramian matrix for powers of x. It arises in the least squares approximation of arbitrary functions by ...

  8. Symplectic matrix - Wikipedia

    en.wikipedia.org/wiki/Symplectic_matrix

    Symplectic matrix. In mathematics, a symplectic matrix is a matrix with real entries that satisfies the condition. (1) where denotes the transpose of and is a fixed nonsingular, skew-symmetric matrix. This definition can be extended to matrices with entries in other fields, such as the complex numbers, finite fields, p -adic numbers, and ...

  9. Jacobian matrix and determinant - Wikipedia

    en.wikipedia.org/wiki/Jacobian_matrix_and...

    In vector calculus, the Jacobian matrix (/ dʒəˈkoʊbiən /, [1][2][3] / dʒɪ -, jɪ -/) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. When this matrix is square, that is, when the function takes the same number of variables as input as the number of vector components of its output ...