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  2. Jacobian matrix and determinant - Wikipedia

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

    When m = 1, that is when f : R n → R is a scalar-valued function, the Jacobian matrix reduces to the row vector; this row vector of all first-order partial derivatives of f is the transpose of the gradient of f, i.e. =.

  3. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    In linear algebra, linear transformations can be represented by matrices.If is a linear transformation mapping to and is a column vector with entries, then there exists an matrix , called the transformation matrix of , [1] such that: = Note that has rows and columns, whereas the transformation is from to .

  4. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    In Matlab/GNU Octave a matrix A can be vectorized by A(:). GNU Octave also allows vectorization and half-vectorization with vec(A) and vech(A) respectively. Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions.

  5. Matrix-free methods - Wikipedia

    en.wikipedia.org/wiki/Matrix-free_methods

    To avoid this expense, matrix-free methods are employed. In order to remove the need to calculate the Jacobian, the Jacobian vector product is formed instead, which is in fact a vector itself. Manipulating and calculating this vector is easier than working with a large matrix or linear system.

  6. Outer product - Wikipedia

    en.wikipedia.org/wiki/Outer_product

    When a vector has only zeros and ones as entries, it is called a logical vector, a special case of a logical matrix. The logical operation and takes the place of multiplication. The outer product of two logical vectors ( u i ) and ( v j ) is given by the logical matrix ( a i j ) = ( u i ∧ v j ) {\displaystyle \left(a_{ij}\right)=\left(u_{i ...

  7. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2). In mathematics , the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations , namely those whose matrix is positive-semidefinite .

  8. List of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical-analysis...

    It provides a rich Excel-like user interface and its built-in vector programming language FPScript has a syntax similar to MATLAB. FreeMat, an open-source MATLAB-like environment with a GPL license. GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command-line interface for solving ...

  9. Matrix (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Matrix_(mathematics)

    When vectors are involved, the terms row vector and column vector are commonly used instead. A matrix with the same number of rows and columns is called a square matrix. [5] A matrix with an infinite number of rows or columns (or both) is called an infinite matrix.