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  2. Table of keyboard shortcuts - Wikipedia

    en.wikipedia.org/wiki/Table_of_keyboard_shortcuts

    For the first two shortcuts going backwards is done by using the right ⇧ Shift key instead of the left. ⌘ Cmd+Space (not MBR) Configure desired keypress in Keyboard and Mouse Preferences, Keyboard Shortcuts, Select the next source in Input menu. [1] Ctrl+Alt+K via KDE Keyboard. Alt+⇧ Shift in GNOME. Ctrl+\ Ctrl+Space: Print Ctrl+P: ⌘ ...

  3. Row and column vectors - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_vectors

    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.) The transpose (indicated by T) of any row vector is a column vector, and the transpose of any column vector is a row vector: […] = [] and [] = […].

  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. In-place matrix transposition - Wikipedia

    en.wikipedia.org/wiki/In-place_matrix_transposition

    Typically, the matrix is assumed to be stored in row-major or column-major order (i.e., contiguous rows or columns, respectively, arranged consecutively). Performing an in-place transpose (in-situ transpose) is most difficult when N ≠ M , i.e. for a non-square (rectangular) matrix, where it involves a complex permutation of the data elements ...

  6. Vectorization (mathematics) - Wikipedia

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

    Programming languages that implement matrices may have easy means for vectorization. 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.

  7. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.

  8. APL syntax and symbols - Wikipedia

    en.wikipedia.org/wiki/APL_syntax_and_symbols

    Some APL interpreters support the compose operator ∘ and the commute operator ⍨. The former ∘ glues functions together so that foo∘bar , for example, could be a hypothetical function that applies defined function foo to the result of defined function bar ; foo and bar can represent any existing function.

  9. Raising and lowering indices - Wikipedia

    en.wikipedia.org/wiki/Raising_and_lowering_indices

    Concretely, in the case where the vector space has an inner product, in matrix notation these can be thought of as row vectors, which give a number when applied to column vectors. We denote this by V ∗ := Hom ( V , K ) {\displaystyle V^{*}:={\text{Hom}}(V,K)} , so that α ∈ V ∗ {\displaystyle \alpha \in V^{*}} is a linear map α : V → K ...