一般性的奇异值分解算法，float浮点型。-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,