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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.
Let H be a Hadamard matrix of order n.The transpose of H is closely related to its inverse.In fact: = where I n is the n × n identity matrix and H T is the transpose of H.To see that this is true, notice that the rows of H are all orthogonal vectors over the field of real numbers and each have length .
In finite-dimensional spaces, the matrix representation (with respect to an orthonormal basis) of an orthogonal transformation is an orthogonal matrix. Its rows are mutually orthogonal vectors with unit norm, so that the rows constitute an orthonormal basis of V. The columns of the matrix form another orthonormal basis of V.
Equivalently, a matrix A is orthogonal if its transpose is equal to its inverse: =, which entails = =, where I is the identity matrix. An orthogonal matrix A is necessarily invertible (with inverse A −1 = A T), unitary (A −1 = A*), and normal (A*A = AA*). The determinant of any orthogonal matrix is either +1 or −1.
Equivalently, it is the group of n × n orthogonal matrices, where the group operation is given by matrix multiplication (an orthogonal matrix is a real matrix whose inverse equals its transpose). The orthogonal group is an algebraic group and a Lie group. It is compact. The orthogonal group in dimension n has two connected components.
The matrix of the linear map mapping the vector of the entries of a matrix to the vector of a part of the entries (for example the vector of the entries that are not below the main diagonal) See vectorization: Exchange matrix: The binary matrix with ones on the anti-diagonal, and zeroes everywhere else. a ij = δ n+1−i,j: A permutation matrix.
In example if , and , are two arbitrary selected elements from the same column q of matrix, then, matrix consists one fours of elements (,,,,,), for which are satisfied the equations , =, and , =,. This property, named “Tr-property” is specific to T r {\displaystyle Tr} matrices.
The exponential representation of an orthogonal matrix of order can also be obtained starting from the fact that in dimension any special orthogonal matrix can be written as =, where is orthogonal and S is a block diagonal matrix with ⌊ / ⌋ blocks of order 2, plus one of order 1 if is odd; since each single block of order 2 is also an ...