enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Rank–nullity theorem - Wikipedia

    en.wikipedia.org/wiki/Ranknullity_theorem

    Rank–nullity theorem. The rank–nullity theorem is a theorem in linear algebra, which asserts: the number of columns of a matrix M is the sum of the rank of M and the nullity of M; and; the dimension of the domain of a linear transformation f is the sum of the rank of f (the dimension of the image of f) and the nullity of f (the dimension of ...

  3. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    For example, the 3 × 3 matrix in the example above has rank two. [9] The rank of a matrix is also equal to the dimension of the column space. The dimension of the null space is called the nullity of the matrix, and is related to the rank by the following equation:

  4. Kernel (linear algebra) - Wikipedia

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

    In the case where V is finite-dimensional, this implies the rank–nullity theorem: ⁡ (⁡) + ⁡ (⁡) = ⁡ (). where the term rank refers to the dimension of the image of L, ⁡ (⁡), while nullity refers to the dimension of the kernel of L, ⁡ (⁡). [4] That is, ⁡ = ⁡ (⁡) ⁡ = ⁡ (⁡), so that the rank–nullity theorem can be ...

  5. Quotient space (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Quotient_space_(linear...

    An immediate corollary, for finite-dimensional spaces, is the rank–nullity theorem: the dimension of V is equal to the dimension of the kernel (the nullity of T) plus the dimension of the image (the rank of T). The cokernel of a linear operator T : V → W is defined to be the quotient space W/im(T).

  6. Rank (linear algebra) - Wikipedia

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

    A matrix is said to have full rank if its rank equals the largest possible for a matrix of the same dimensions, which is the lesser of the number of rows and columns. A matrix is said to be rank-deficient if it does not have full rank. The rank deficiency of a matrix is the difference between the lesser of the number of rows and columns, and ...

  7. Jordan normal form - Wikipedia

    en.wikipedia.org/wiki/Jordan_normal_form

    By the rank-nullity theorem, dim(ker(A−λI))=n-r, so t=n-r-s, and so the number of vectors in the potential basis is equal to n. To show linear independence, suppose some linear combination of the vectors is 0.

  8. Schmidt decomposition - Wikipedia

    en.wikipedia.org/wiki/Schmidt_decomposition

    Consider a vector of the tensor product . in the form of Schmidt decomposition = =. Form the rank 1 matrix =.Then the partial trace of , with respect to either system A or B, is a diagonal matrix whose non-zero diagonal elements are | |.

  9. Nullity (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Nullity_(graph_theory)

    The nullity of M is given by m − n + c, where, c is the number of components of the graph and n − c is the rank of the oriented incidence matrix. This name is rarely used; the number is more commonly known as the cycle rank, cyclomatic number, or circuit rank of the graph. It is equal to the rank of the cographic matroid of the graph.