On a Variational Formulation of the Generalized Singular Value Decomposition
Moody T. Chu, Robert E. Funderlic, Gene Howard Golub · SIAM Journal on Matrix Analysis and Applications · 1997
A variational formulation for the generalized singular value decomposition (GSVD) of a pair of matrices $A \in R^{m \times n}$ and $B \in R^{p \times n}$ is presented. In particular, a duality theory analogous to that of the SVD provides new understanding of left and right generalized singular vectors. It is shown that the intersection of row spaces of A and B plays a key role in the GSVD duality theory. The main result that characterizes left GSVD vectors involves a generalized singular value deflation process.