When.com Web Search

  1. Ads

    related to: attributes of a singular matrix worksheet printable grade

Search results

  1. Results From The WOW.Com Content Network
  2. Singular value - Wikipedia

    en.wikipedia.org/wiki/Singular_value

    The smallest singular value of a matrix A is σ n (A). It has the following properties for a non-singular matrix A: The 2-norm of the inverse matrix (A −1) equals the inverse σ n −1 (A). [2]: Thm.3.3 The absolute values of all elements in the inverse matrix (A −1) are at most the inverse σ n −1 (A). [2]: Thm.3.3

  3. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    Consequently, if all singular values of a square matrix ⁠ ⁠ are non-degenerate and non-zero, then its singular value decomposition is unique, up to multiplication of a column of ⁠ ⁠ by a unit-phase factor and simultaneous multiplication of the corresponding column of ⁠ ⁠ by the same unit-phase factor.

  4. Singular matrices - Wikipedia

    en.wikipedia.org/?title=Singular_matrices&...

    If Singular matrix is retargeted or is expanded into a separate article, template, or other project page, this redirect will be recategorized to be updated. From the plural form : This is a redirect from a plural noun to its singular form or to a broader article; the singular form is "Singular matrix".

  5. List of named matrices - Wikipedia

    en.wikipedia.org/wiki/List_of_named_matrices

    Equivalently, a matrix with singular values that are either 0 or 1. Singular matrix: A square matrix that is not invertible. Unimodular matrix: An invertible matrix with entries in the integers (integer matrix) Necessarily the determinant is +1 or −1. Unipotent matrix: A square matrix with all eigenvalues equal to 1. Equivalently, A − I is ...

  6. Spectrum of a matrix - Wikipedia

    en.wikipedia.org/wiki/Spectrum_of_a_matrix

    The determinant of the matrix equals the product of its eigenvalues. Similarly, the trace of the matrix equals the sum of its eigenvalues. [4] [5] [6] From this point of view, we can define the pseudo-determinant for a singular matrix to be the product of its nonzero eigenvalues (the density of multivariate normal distribution will need this ...

  7. Matrix norm - Wikipedia

    en.wikipedia.org/wiki/Matrix_norm

    Suppose a vector norm ‖ ‖ on and a vector norm ‖ ‖ on are given. Any matrix A induces a linear operator from to with respect to the standard basis, and one defines the corresponding induced norm or operator norm or subordinate norm on the space of all matrices as follows: ‖ ‖, = {‖ ‖: ‖ ‖ =} = {‖ ‖ ‖ ‖:} . where denotes the supremum.