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Livre :
Expressions régulières,
Syntaxe et mise en oeuvre :
GNU/Linux |
CentOS 4.8 |
i386 |
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dlasd1(l) |
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DLASD1 - compute the SVD of an upper bidiagonal N-by-M matrix B,
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SUBROUTINE DLASD1( |
NL, NR, SQRE, D, ALPHA, BETA, U, LDU, VT, LDVT, IDXQ, IWORK, WORK, INFO ) | ||
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INTEGER |
INFO, LDU, LDVT, NL, NR, SQRE | ||
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DOUBLE |
PRECISION ALPHA, BETA | ||
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INTEGER |
IDXQ( * ), IWORK( * ) | ||
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DOUBLE |
PRECISION D( * ), U( LDU, * ), VT( LDVT, * ), WORK( * ) |
DLASD1 computes the SVD of an upper bidiagonal N-by-M matrix B, where N = NL + NR + 1 and M = N + SQRE. DLASD1 is called from DLASD0.
A related subroutine DLASD7 handles the case in which the singular values (and the singular vectors in factored form) are desired.
DLASD1 computes the SVD as follows:
( D1(in) 0 0 0
)
B = U(in) * ( Z1’ a Z2’ b ) * VT(in)
( 0 0 D2(in) 0 )
= U(out) * ( D(out) 0) * VT(out)
where Z’ = (Z1’ a Z2’ b) = u’ VT’, and u is a vector of dimension M with ALPHA and BETA in the NL+1 and NL+2 th entries and zeros elsewhere; and the entry b is empty if SQRE = 0.
The left singular vectors of the original matrix are stored in U, and the transpose of the right singular vectors are stored in VT, and the singular values are in D. The algorithm consists of three stages:
The first stage
consists of deflating the size of the problem
when there are multiple singular values or when there are
zeros in
the Z vector. For each such occurence the dimension of the
secular equation problem is reduced by one. This stage is
performed by the routine DLASD2.
The second
stage consists of calculating the updated
singular values. This is done by finding the square roots of
the
roots of the secular equation via the routine DLASD4 (as
called
by DLASD3). This routine also calculates the singular
vectors of
the current problem.
The final stage
consists of computing the updated singular vectors
directly using the updated singular values. The singular
vectors
for the current problem are multiplied with the singular
vectors
from the overall problem.
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an
NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular
matrix.
The bidiagonal matrix has row dimension N = NL + NR + 1, and column dimension M = N + SQRE.
D (input/output) DOUBLE PRECISION array,
dimension (N = NL+NR+1). On
entry D(1:NL,1:NL) contains the singular values of the
upper block; and D(NL+2:N) contains the singular values of
the lower block. On exit D(1:N) contains the singular values
of the modified matrix.
ALPHA (input) DOUBLE PRECISION
Contains the diagonal element associated with the added row.
BETA (input) DOUBLE PRECISION
Contains the off-diagonal element associated with the added row.
U (input/output) DOUBLE PRECISION array, dimension(LDU,N)
On entry U(1:NL, 1:NL) contains
the left singular vectors of
the upper block; U(NL+2:N, NL+2:N) contains the left
singular vectors of the lower block. On exit U contains the
left singular vectors of the bidiagonal matrix.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= max( 1, N ).
VT (input/output) DOUBLE PRECISION array, dimension(LDVT,M)
where M = N + SQRE. On entry
VT(1:NL+1, 1:NL+1)’ contains the right singular
vectors of the upper block; VT(NL+2:M, NL+2:M)’
contains the right singular vectors of the lower block. On
exit VT’ contains the right singular vectors of the
bidiagonal matrix.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= max( 1, M ).
IDXQ (output) INTEGER array, dimension(N)
This contains the permutation which will reintegrate the subproblem just solved back into sorted order, i.e. D( IDXQ( I = 1, N ) ) will be in ascending order.
IWORK (workspace) INTEGER
array, dimension( 4 * N )
WORK (workspace) DOUBLE PRECISION array, dimension( 3*M**2 +
2*M )
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal
value.
> 0: if INFO = 1, an singular value did not converge
Based on
contributions by
Ming Gu and Huan Ren, Computer Science Division, University
of
California at Berkeley, USA
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dlasd1(l) | |