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Text File | 1994-02-21 | 1.2 KB | 48 lines | [TEXT/RLAB] |
- 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
-