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  2. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    The conjugate gradient method with a trivial modification is extendable to solving, given complex-valued matrix A and vector b, the system of linear equations = for the complex-valued vector x, where A is Hermitian (i.e., A' = A) and positive-definite matrix, and the symbol ' denotes the conjugate transpose.

  3. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    Specifically, the singular value decomposition of an complex matrix ⁠ ⁠ is a factorization of the form =, where ⁠ ⁠ is an ⁠ ⁠ complex unitary matrix, is an rectangular diagonal matrix with non-negative real numbers on the diagonal, ⁠ ⁠ is an complex unitary matrix, and is the conjugate transpose of ⁠ ⁠. Such decomposition ...

  4. Transpose - Wikipedia

    en.wikipedia.org/wiki/Transpose

    In linear algebra, the transpose of a matrix is an operator which flips a matrix over its diagonal; that is, it switches the row and column indices of the matrix A by producing another matrix, often denoted by A T (among other notations). [1] The transpose of a matrix was introduced in 1858 by the British mathematician Arthur Cayley. [2]

  5. Root locus analysis - Wikipedia

    en.wikipedia.org/wiki/Root_locus_analysis

    The following MATLAB code will plot the root locus of the closed-loop transfer function as varies using the described manual method as well as the rlocus built-in function: % Manual method K_array = ( 0 : 0.1 : 220 ). ' ; % .' is a transpose.

  6. Transpositions matrix - Wikipedia

    en.wikipedia.org/wiki/Transpositions_matrix

    In [5] are given as examples code of a Matlab functions that creates and matrices for vector of size n = 2, 4, or, 8. Stay open question is it possible to create T r s {\displaystyle Trs} matrices of size, greater than 8.

  7. Hessian matrix - Wikipedia

    en.wikipedia.org/wiki/Hessian_matrix

    Suppose : is a function taking as input a vector and outputting a scalar (). If all second-order partial derivatives of exist, then the Hessian matrix of is a square matrix, usually defined and arranged as = [].

  8. Laplacian matrix - Wikipedia

    en.wikipedia.org/wiki/Laplacian_matrix

    In the matrix notation, the adjacency matrix of the undirected graph could, e.g., be defined as a Boolean sum of the adjacency matrix of the original directed graph and its matrix transpose, where the zero and one entries of are treated as logical, rather than numerical, values, as in the following example:

  9. Conjugate transpose - Wikipedia

    en.wikipedia.org/wiki/Conjugate_transpose

    The conjugate transpose of a matrix with real entries reduces to the transpose of , as the conjugate of a real number is the number itself. The conjugate transpose can be motivated by noting that complex numbers can be usefully represented by 2 × 2 {\displaystyle 2\times 2} real matrices, obeying matrix addition and multiplication: a + i b ≡ ...