16 December 1989 Canonical Correlations And Generalized SVD: Applications And New Algorithms
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Abstract
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.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. Magnus Ewerbring, Franklin T. Luk, "Canonical Correlations And Generalized SVD: Applications And New Algorithms", Proc. SPIE 0977, Real-Time Signal Processing XI, (16 December 1989); doi: 10.1117/12.948572; https://doi.org/10.1117/12.948572
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