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)
 
 