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  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. 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.

  4. Rank (graph theory) - Wikipedia

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

    Equivalently, the rank of a graph is the rank of the oriented incidence matrix associated with the graph. [2] Analogously, the nullity of the graph is the nullity of its oriented incidence matrix, given by the formula m − n + c, where n and c are as above and m is the number of edges in the graph. The nullity is equal to the first Betti ...

  5. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The dimension of the row space is called the rank of the matrix. This is the same as the maximum number of linearly independent rows that can be chosen from the matrix, or equivalently the number of pivots. 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.

  6. Rank (linear algebra) - Wikipedia

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

    The rank of a matrix plus the nullity of the matrix equals the number of columns of the matrix. (This is the rank–nullity theorem.) If A is a matrix over the real numbers then the rank of A and the rank of its corresponding Gram matrix are equal.

  7. 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 ...

  8. Category:Isomorphism theorems - Wikipedia

    en.wikipedia.org/wiki/Category:Isomorphism_theorems

    These theorems are generalizations of some of the fundamental ideas from linear algebra, notably the rank–nullity theorem, and are encountered frequently in group theory. The isomorphism theorems are also fundamental in the field of K-theory , and arise in ostensibly non-algebraic situations such as functional analysis (in particular the ...

  9. Circuit rank - Wikipedia

    en.wikipedia.org/wiki/Circuit_rank

    The circuit rank of a hypergraph can be derived by its Levi graph, with the same circuit rank but reduced to a simple graph. r = g + c − ( v + e ) {\displaystyle r=g+c-(v+e)} where g is the degree sum , e is the number of edges in the given graph, v is the number of vertices , and c is the number of connected components .