<< slicot_ag08bd | SLICOT | slicot_mb03od >> |
[RANK_OUT, C_OUT, S, X, IWARN, INFO] = slicot_mb02md(JOB, M, N, L, RANK_IN, C_IN, TOL) |
Determines whether the values of the parameters RANK and TOL are to be specified by the user or computed by the routine as follows: = 'R': Compute RANK only; = 'T': Compute TOL only; = 'B': Compute both RANK and TOL; = 'N': Compute neither RANK nor TOL.
The number of rows in the data matrix A and the observation matrix B.
The number of columns in the data matrix A.
The number of columns in the observation matrix B.
if JOB = 'T' or JOB = 'N', then RANK must specify r, the rank of the TLS approximation [A + DA | B + DB].
the leading M-by-(N+L) part of this array must contain the matrices A and B.
A tolerance used to determine the rank of the TLS approximation [A+DA|B+DB] and to check the multiplicity of the singular values of matrix C.
if JOB = 'R' or JOB = 'B', and INFO = 0, then RANK contains the computed (effective) rank of the TLS approximation [A + DA | B + DB].
the leading (N+L)-by-(N+L) part of this array contains the (transformed) right singular vectors, including null space vectors, if any, of C = [A | B].
If INFO = 0, the singular values of matrix C
If INFO = 0, the leading N-by-L part of this array contains the solution X to the TLS problem specified by A and B.
= 0: no warnings; = 1: if the rank of matrix C has been lowered because a singular value of multiplicity greater than 1 was found; = 2: if the rank of matrix C has been lowered because the upper triangular matrix F is (numerically) singular.
= 0: successful exit;
To solve the Total Least Squares (TLS) problem using a Singular Value Decomposition (SVD) approach. The TLS problem assumes an overdetermined set of linear equations AX = B, where both the data matrix A as well as the observation matrix B are inaccurate. The routine also solves determined and underdetermined sets of equations by computing the minimum norm solution. It is assumed that all preprocessing measures (scaling, coordinate transformations, whitening, ... ) of the data have been performed in advance.
M = 6;
N = 3;
L = 1;
JOB = 'B';
TOL = 0.0;
RANK_IN = 1;
C_IN = [0.80010 0.39985 0.60005 0.89999;
0.29996 0.69990 0.39997 0.82997;
0.49994 0.60003 0.20012 0.79011;
0.90013 0.20016 0.79995 0.85002;
0.39998 0.80006 0.49985 0.99016;
0.20002 0.90007 0.70009 1.02994];
[RANK_OUT, C_OUT, S, X, IWARN, INFO] = slicot_mb02md(JOB, M, N, L, RANK_IN, C_IN, TOL)
Version | Description |
---|---|
1.0.0 | initial version |
SLICOT Documentation