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  2. EP matrix - Wikipedia

    en.wikipedia.org/wiki/EP_matrix

    This is similar to the characterization of normal matrices where A commutes with its conjugate transpose. [4] As a corollary, nonsingular matrices are always EP matrices. The sum of EP matrices A i is an EP matrix if the null-space of the sum is contained in the null-space of each matrix A i .

  3. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    For example, if the row space is a plane through the origin in three dimensions, then the null space will be the perpendicular line through the origin. This provides a proof of the rank–nullity theorem (see dimension above). The row space and null space are two of the four fundamental subspaces associated with a matrix A (the other two being ...

  4. Kernel (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(linear_algebra)

    The left null space, or cokernel, of a matrix A consists of all column vectors x such that x T A = 0 T, where T denotes the transpose of a matrix. The left null space of A is the same as the kernel of A T. The left null space of A is the orthogonal complement to the column space of A, and is dual to the cokernel of the

  5. Shift matrix - Wikipedia

    en.wikipedia.org/wiki/Shift_matrix

    Clearly, the transpose of a lower shift matrix is an upper shift matrix and vice versa. As a linear transformation , a lower shift matrix shifts the components of a column vector one position down, with a zero appearing in the first position.

  6. In-place matrix transposition - Wikipedia

    en.wikipedia.org/wiki/In-place_matrix_transposition

    For example, software libraries for linear algebra, such as BLAS, typically provide options to specify that certain matrices are to be interpreted in transposed order to avoid data movement. However, there remain a number of circumstances in which it is necessary or desirable to physically reorder a matrix in memory to its transposed ordering.

  7. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)

  8. Invariant subspace - Wikipedia

    en.wikipedia.org/wiki/Invariant_subspace

    As the above examples indicate, the invariant subspaces of a given linear transformation T shed light on the structure of T. When V is a finite-dimensional vector space over an algebraically closed field , linear transformations acting on V are characterized (up to similarity) by the Jordan canonical form , which decomposes V into invariant ...

  9. Transpose of a linear map - Wikipedia

    en.wikipedia.org/wiki/Transpose_of_a_linear_map

    In the language of category theory, taking the dual of vector spaces and the transpose of linear maps is therefore a contravariant functor from the category of vector spaces over to itself. One can identify t ( t u ) {\displaystyle {}^{t}\left({}^{t}u\right)} with u {\displaystyle u} using the natural injection into the double dual.