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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. [6]

  3. Conjunctive query - Wikipedia

    en.wikipedia.org/wiki/Conjunctive_Query

    This formula cannot be implemented in the select-project-join fragment of relational algebra, and hence should not be considered a conjunctive query. Conjunctive queries can express a large proportion of queries that are frequently issued on relational databases. To give an example, imagine a relational database for storing information about ...

  4. SQL syntax - Wikipedia

    en.wikipedia.org/wiki/SQL_syntax

    SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar. Insignificant whitespace is generally ignored in SQL statements and queries, making it easier to format SQL code for readability.

  5. 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

  6. 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 ...

  7. QR decomposition - Wikipedia

    en.wikipedia.org/wiki/QR_decomposition

    If instead A is a complex square matrix, then there is a decomposition A = QR where Q is a unitary matrix (so the conjugate transpose † =). If A has n linearly independent columns, then the first n columns of Q form an orthonormal basis for the column space of A.

  8. Zero-forcing precoding - Wikipedia

    en.wikipedia.org/wiki/Zero-forcing_precoding

    Note that differently from the feedback bits case, the required feedback resource is a function of both downlink and uplink channel conditions. It is reasonable to include the uplink channel status in the calculation of the feedback resource since the uplink channel status determines the capacity, i.e., bits/second per unit frequency band (Hz ...

  9. Moore–Penrose inverse - Wikipedia

    en.wikipedia.org/wiki/Moore–Penrose_inverse

    For example, in the MATLAB or GNU Octave function pinv, the tolerance is taken to be t = ε⋅max(m, n)⋅max(Σ), where ε is the machine epsilon. The computational cost of this method is dominated by the cost of computing the SVD, which is several times higher than matrix–matrix multiplication, even if a state-of-the art implementation ...