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  2. Kernel (linear algebra) - Wikipedia

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

    A basis of the kernel of A consists in the non-zero columns of C such that the corresponding column of B is a zero column. In fact, the computation may be stopped as soon as the upper matrix is in column echelon form: the remainder of the computation consists in changing the basis of the vector space generated by the columns whose upper part is ...

  3. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    Also finding a basis for the column space of A is equivalent to finding a basis for the row space of the transpose matrix A T. To find the basis in a practical setting (e.g., for large matrices), the singular-value decomposition is typically used.

  4. Metric signature - Wikipedia

    en.wikipedia.org/wiki/Metric_signature

    In mathematics, the signature (v, p, r) [clarification needed] of a metric tensor g (or equivalently, a real quadratic form thought of as a real symmetric bilinear form on a finite-dimensional vector space) is the number (counted with multiplicity) of positive, negative and zero eigenvalues of the real symmetric matrix g ab of the metric tensor with respect to a basis.

  5. Basis (linear algebra) - Wikipedia

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

    The common feature of the other notions is that they permit the taking of infinite linear combinations of the basis vectors in order to generate the space. This, of course, requires that infinite sums are meaningfully defined on these spaces, as is the case for topological vector spaces – a large class of vector spaces including e.g. Hilbert ...

  6. Rank–nullity theorem - Wikipedia

    en.wikipedia.org/wiki/Rank–nullity_theorem

    The second proof [6] looks at the homogeneous system =, where is a with rank, and shows explicitly that there exists a set of linearly independent solutions that span the null space of . While the theorem requires that the domain of the linear map be finite-dimensional, there is no such assumption on the codomain.

  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. Change of basis - Wikipedia

    en.wikipedia.org/wiki/Change_of_basis

    A change of bases is defined by an m×m change-of-basis matrix P for V, and an n×n change-of-basis matrix Q for W. On the "new" bases, the matrix of T is . This is a straightforward consequence of the change-of-basis formula.

  9. Null space (matrix) - Wikipedia

    en.wikipedia.org/?title=Null_space_(matrix...

    Null space (matrix) Add languages. Add links. ... Download as PDF; Printable version; In other projects ... From Wikipedia, the free encyclopedia. Redirect page ...

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