SVD SVD Singular Value Decomposition of a Matrix

Usage

Computes the singular value decomposition (SVD) of a matrix.  The 
svd function has three forms.  The first returns only the singular
values of the matrix:

  s = svd(A)

The second form returns both the singular values in a diagonal
matrix S, as well as the left and right eigenvectors.

  [U,S,V] = svd(A)

The third form returns a more compact decomposition, with the
left and right singular vectors corresponding to zero singular
values being eliminated.  The syntax is

  [U,S,V] = svd(A,0)