SGGSVD computes the generalized singular value decomposition (GSVD) * of an M-by-N real matrix A and P-by-N real matrix B: * * U*A*Q = D1*( 0 R ), V*B*Q = D2*( 0 R ) * * where U, V and Q are orthogonal matrices, and Z is the transpose * of Z. Let K+L = the effective numerical rank of the matrix (A ,B ) , * then R is a K+L-by-K+L nonsingular upper triangular matrix, D1 and * D2 are M-by-(K+L) and P-by-(K+L) "diagonal" matrices and of the * following structures,

single\sgeqpf.f
......\sgeqr2.f
......\sgerq2.f
......\sggsvd.f
......\sggsvp.f
......\slacpy.f
......\slags2.f
......\slange.f
......\slapll.f
......\slapmt.f
......\slapy2.f
......\slarf.f
......\slarfg.f
......\slartg.f
......\slas2.f
......\slaset.f
......\slassq.f
......\slasv2.f
......\sorg2r.f
......\sorm2r.f
......\sormr2.f
......\stgsja.f
single

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