svd:

Syntax:	svd ( A )
	svd ( A , TYPE )

Description:

	Computes the singular values of the input matrix A, as well as
	the right and left singular vectors in various forms. Where:

		A = U * diag (sigma) * Vt

	The output is a list containing the three afore-mentioned
	objects (u, sigma, vt).  Various forms of the right and left
	singular vectors can be computed, depending upon the value of
	the second argument, TYPE.

	TYPE:	`"S"'	A minimal version of U, and V' are returned.
			This is the default.
	TYPE:	`"A"'	The full U, and V' are returned.
	TYPE:	`"N"'	U and V' are not computed, empty U and V' are
			returned. 

	The LAPACK subroutine DGESVD, or ZGESVD is used to perform the
	computation.

	Example:

	> A = [0.96, 1.72; 2.28, 0.96];
	> Asvd = svd(A)
	   sigma        u            vt
	> Asvd.vt
	 matrix columns 1 thru 2
	        -0.8        -0.6
	         0.6        -0.8
	> Asvd.u
	 matrix columns 1 thru 2
	        -0.6        -0.8
	        -0.8         0.6
	> Asvd.sigma
	 vector elements 1 thru 2
	           3           1
	> check = Asvd.u * diag(Asvd.sigma) * Asvd.vt
	 check =
	 matrix columns 1 thru 2
	        0.96        1.72
	        2.28        0.96
