a square matrix that is equal to its transpose
The transpose of a matrix A is the matrix B that is obtained by swapping the rows and columns of A into the columns and rows of B. In algebraic form, if A = {aij} then B = {aji} is its transpose, where 1 ≤ i ≤ n and 1 ≤ j ≤ m.
The classical adjoint of a square matrix A the transpose of the matrix who (i, j) entry is the a i j cofactor.
It need not be, so the question makes no sense!
A matrix A is orthogonal if itstranspose is equal to it inverse. So AT is the transpose of A and A-1 is the inverse. We have AT=A-1 So we have : AAT= I, the identity matrix Since it is MUCH easier to find a transpose than an inverse, these matrices are easy to compute with. Furthermore, rotation matrices are orthogonal. The inverse of an orthogonal matrix is also orthogonal which can be easily proved directly from the definition.
yes, it is true that the transpose of the transpose of a matrix is the original matrix
The Transpose of a MatrixThe matrix of order n x m obtained by interchanging the rows and columns of the m X n matrix, A, is called the transpose of A and is denoted by A' or AT.
a square matrix that is equal to its transpose
Another sparse matrix.
A fast-transpose is a computer algorithm that quickly transposes a sparse matrix using a relatively small amount of memory. Using arrays normally to record a sparse matrix uses up a lot of memory since many of the matrix's values are zero. In addition, using the normal transpose algorithm to transpose this matrix will take O(cols*elements) amount of time. The fast-transpose algorithm only uses a little memory to record the matrix and takes only O(cols+elements) amount of time, which is efficient considering the number of elements equals cols*rows.
Invert rows and columns to get the transpose of a matrix
The transpose of a matrix A is the matrix B that is obtained by swapping the rows and columns of A into the columns and rows of B. In algebraic form, if A = {aij} then B = {aji} is its transpose, where 1 ≤ i ≤ n and 1 ≤ j ≤ m.
The classical adjoint of a square matrix A the transpose of the matrix who (i, j) entry is the a i j cofactor.
Hermitian matrix (please note spelling): a square matrix with complex elements that is equal to its conjugate transpose.
transpose(Matrix mat,int rows, int cols ){ //construction step Matrix tmat; for(int i=0;i<rows;i++){ for(int j=0;j<cols;j++){ tmat[j][i] = mat[i][j]; } } }
It need not be, so the question makes no sense!
It is the conjugate transpose of the matrix. Of course the conjugate parts only matters with complex entries. So here is a definition:A unitary matrix is a square matrix U whose entries are complex numbers and whose inverse is equal to its conjugate transpose U*. This means thatU*U = UU* = I. Where I is the identity matrix.