Canonical Correlations And Generalized SVD: Applications And New Algorithms
L. Magnus Ewerbring, Franklin T. Luk · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1989
In this paper we consider canonical correlations and a generalization of the singular value decomposition (SVD) that involves three matrices. We show how the two matrix problems are related and how they can be used in important applications such as weighted least squares and optimal prediction. We present two new computational procedures for the problems based on implicit SVD methods for triple matrix products. Our algorithms are well suited for parallel implementation.