function [U, S, V] = piro_band_svd(A, econ)
% Find the Singular Value Decomposition of a band matrix in sparse/full format.
% Usage:
%          S = piro_band_svd(A) ;
% The singular values of the band matrix A, are returned in the vector S.
%
%          [U, S, VT] = piro_band_svd(A) ;
% Computes the Singular value decomposition of the band matrix A. S is the
% diagonal matrix with singular values in the diagonal. U and VT are the left
% and right singular vectors. This computes the full SVD. U is mxm and VT is
% nxn. 
%
%          [U, S, VT] = piro_band_svd(A, econ) ;
% Computes the thin Singular value decomposition of the band matrix A. S is the
% diagonal matrix with singular values in the diagonal. U and VT are the left
% and right singular vectors. If m > n U is mxn and VT is nxn. If m <= n then
% it is the same as full SVD.
% A can be real/complex in all the cases. 
%

%   Copyright 2009, Sivasankaran Rajamanickam, Timothy A. Davis
%   http://www.cise.ufl.edu/research/sparse

    error ('piro_band_svd is missing \n')