This is equivalent to saying that A times its transpose must be the identity matrix.
Columns of the identity matrix are added as column vectors for these variables.
It can be verified that the above set of points has mean and covariance (the identity matrix).
Imagine a simple loop that sets an array to the identity matrix.
It is consequently a square root of the identity matrix.
The identity matrix has nothing but zeroes except on the main diagonal, where there are all ones.
There is exactly one identity matrix for each square dimension set.
The second matrix is the identity matrix and has no effect on the product.
Let the noise vector be normally distributed as where is an identity matrix.
Nucleotide sequences use the identity matrix for the same purpose.