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The matrix and its transpose have the same characteristic polynomial. A {\displaystyle A} is similar to a triangular matrix if and only if its characteristic polynomial can be completely factored into linear factors over K {\displaystyle K} (the same is true with the minimal polynomial instead of the characteristic polynomial).
In linear algebra, the transpose of a matrix is an operator which flips a matrix over its diagonal; that is, it switches the row and column indices of the matrix A by producing another matrix, often denoted by A T (among other notations). [1] The transpose of a matrix was introduced in 1858 by the British mathematician Arthur Cayley. [2]
matrix is symmetric matrix.; matrix is persymmetric matrix, i.e. it is symmetric with respect to the northeast-to-southwest diagonal too.; Every one row and column of matrix consists all n elements of given vector without repetition.
Visual understanding of multiplication by the transpose of a matrix. If A is an orthogonal matrix and B is its transpose, the ij-th element of the product AA T will vanish if i≠j, because the i-th row of A is orthogonal to the j-th row of A. An orthogonal matrix is the real specialization of a unitary matrix, and thus always a normal matrix.
Adjugate matrix: Transpose of the cofactor matrix: The inverse of a matrix is its adjugate matrix divided by its determinant: Augmented matrix: Matrix whose rows are concatenations of the rows of two smaller matrices: Used for performing the same row operations on two matrices Bézout matrix: Square matrix whose determinant is the resultant of ...
The conjugate transpose of a matrix with real entries reduces to the transpose of , as the conjugate of a real number is the number itself. The conjugate transpose can be motivated by noting that complex numbers can be usefully represented by 2 × 2 {\displaystyle 2\times 2} real matrices, obeying matrix addition and multiplication: a + i b ≡ ...
In mathematics, a Hermitian matrix (or self-adjoint matrix) is a complex square matrix that is equal to its own conjugate transpose—that is, the element in the i-th row and j-th column is equal to the complex conjugate of the element in the j-th row and i-th column, for all indices i and j: = ¯
The transpose of an upper triangular matrix is a lower triangular matrix and vice versa. A matrix which is both symmetric and triangular is diagonal. In a similar vein, a matrix which is both normal (meaning A * A = AA *, where A * is the conjugate transpose) and triangular is also diagonal.