ABSTRACT
One of the most elegant and efficient algorithms for the inversion of a matrix is the singular value decomposition (SVD). If an m × m square matrix X is of full rank, SVD is an efficient method for finding the inverse X−1 . Even if X is an m × n rectangular matrix and is also not of full rank, then SVD is an elegant method of obtaining the rank and the pseudo inverse of X.
