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  2. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The nullity of a matrix is the dimension of the null space, and is equal to the number of columns in the reduced row echelon form that do not have pivots. [7] The rank and nullity of a matrix A with n columns are related by the equation:

  3. Rank–nullity theorem - Wikipedia

    en.wikipedia.org/wiki/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 the kernel of f). [1 ...

  4. Nullity theorem - Wikipedia

    en.wikipedia.org/wiki/Nullity_theorem

    More generally, if a submatrix is formed from the rows with indices {i 1, i 2, …, i m} and the columns with indices {j 1, j 2, …, j n}, then the complementary submatrix is formed from the rows with indices {1, 2, …, N} \ {j 1, j 2, …, j n} and the columns with indices {1, 2, …, N} \ {i 1, i 2, …, i m}, where N is the size of the ...

  5. Rank (linear algebra) - Wikipedia

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

    A fundamental result in linear algebra is that the column rank and the row rank are always equal. (Three proofs of this result are given in § Proofs that column rank = row rank, below.) This number (i.e., the number of linearly independent rows or columns) is simply called the rank of A.

  6. Sparse matrix - Wikipedia

    en.wikipedia.org/wiki/Sparse_matrix

    Then we take slices from V and COL_INDEX starting at row_start and ending at row_end. To extract the row 1 (the second row) of this matrix we set row_start=1 and row_end=2. Then we make the slices V[1:2] = [8] and COL_INDEX[1:2] = [1]. We now know that in row 1 we have one element at column 1 with value 8.

  7. List of named matrices - Wikipedia

    en.wikipedia.org/wiki/List_of_named_matrices

    A row consists of 1, a, a 2, a 3, etc., and each row uses a different variable. Walsh matrix: A square matrix, with dimensions a power of 2, the entries of which are +1 or −1, and the property that the dot product of any two distinct rows (or columns) is zero. Z-matrix: A matrix with all off-diagonal entries less than zero.

  8. Nullity - Wikipedia

    en.wikipedia.org/wiki/Nullity

    Nullity (linear algebra), the dimension of the kernel of a mathematical operator or null space of a matrix; Nullity (graph theory), the nullity of the adjacency matrix of a graph; Nullity, the difference between the size and rank of a subset in a matroid; Nullity, a concept in transreal arithmetic denoted by Φ, or similarly in wheel theory ...

  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.