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  2. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    rank(A) = the maximum number of linearly independent rows or columns of A. [5] If the matrix represents a linear transformation, the column space of the matrix equals the image of this linear transformation. The column space of a matrix A is the set of all linear combinations of the columns in A. If A = [a 1 ⋯ a n], then colsp(A) = span({a 1 ...

  3. Matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication

    A coordinate vector is commonly organized as a column matrix (also called a column vector), which is a matrix with only one column. So, a column vector represents both a coordinate vector, and a vector of the original vector space. A linear map A from a vector space of dimension n into a vector space of dimension m maps a column vector

  4. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    In other words, the matrix of the combined transformation A followed by B is simply the product of the individual matrices. When A is an invertible matrix there is a matrix A −1 that represents a transformation that "undoes" A since its composition with A is the identity matrix. In some practical applications, inversion can be computed using ...

  5. 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.

  6. Strassen algorithm - Wikipedia

    en.wikipedia.org/wiki/Strassen_algorithm

    The left column visualizes the calculations necessary to determine the result of a 2x2 matrix multiplication. Naïve matrix multiplication requires one multiplication for each "1" of the left column. Each of the other columns (M1-M7) represents a single one of the 7 multiplications in the Strassen algorithm.

  7. Projection matrix - Wikipedia

    en.wikipedia.org/wiki/Projection_matrix

    A matrix, has its column space depicted as the green line. The projection of some vector onto the column space of is the vector . From the figure, it is clear that the closest point from the vector onto the column space of , is , and is one where we can draw a line orthogonal to the column space of .

  8. Rule of Sarrus - Wikipedia

    en.wikipedia.org/wiki/Rule_of_Sarrus

    Rule of Sarrus: The determinant of the three columns on the left is the sum of the products along the down-right diagonals minus the sum of the products along the up-right diagonals. In matrix theory , the rule of Sarrus is a mnemonic device for computing the determinant of a 3 × 3 {\displaystyle 3\times 3} matrix named after the French ...

  9. Row and column vectors - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_vectors

    In linear algebra, a column vector with ⁠ ⁠ elements is an matrix [1] consisting of a single column of ⁠ ⁠ entries, for example, = [].. Similarly, a row vector is a matrix for some ⁠ ⁠, consisting of a single row of ⁠ ⁠ entries, = […]. (Throughout this article, boldface is used for both row and column vectors.)