The generalized (or quotient) singular value decomposition
of an m-by-n matrix
A and a p-by-n matrix B is the pair of factorizations
The generalized singular value decomposition is
computed by driver routine xGGSVD (see section 184.108.40.206).
We will give error bounds for the generalized
singular values in the
common case where
be the values of
computed by xGGSVD.
The approximate error
bound4.10for these values is
Here is another way to interpret SERRBD: if we think of and as representing the subspace consisting of the straight line through the origin with slope , and similarly and representing the subspace , then bounds the acute angle between and . Note that any two lines through the origin with nearly vertical slopes (very large ) are close together in angle. (This is related to the chordal distance in section 4.10.1.)
SERRBD can be computed by the following code fragment, which for simplicity assumes . (The assumption r=n implies only that . Error bounds can also be computed when , with slightly more complicated code.)
EPSMCH = SLAMCH( 'E' ) * Compute generalized singular values of A and B CALL SGGSVD( 'N', 'N', 'N', M, N, P, K, L, A, LDA, B, $ LDB, ALPHA, BETA, U, LDU, V, LDV, Q, LDQ, $ WORK, IWORK, INFO ) * Compute rank of [A',B']' RANK = K+L IF( INFO.GT.0 ) THEN PRINT *,'SGGSVD did not converge' ELSE IF( RANK.LT.N ) THEN PRINT *,'[A**T,B**T]**T not full rank' ELSE IF ( M .GE. N .AND. N .GT. 0 ) THEN * Compute reciprocal condition number RCOND of R CALL STRCON( 'I', 'U', 'N', N, A, LDA, RCOND, WORK, IWORK, $ INFO ) RCOND = MAX( RCOND, EPSMCH ) SERRBD = EPSMCH / RCOND END IF
For example4.11, if