Canonical Correlations And Generalized SVD: Applications And New Algorithms

L. Magnus Ewerbring; Franklin T. Luk

doi:10.1117/12.948572

16 December 1989 Canonical Correlations And Generalized SVD: Applications And New Algorithms

L. Magnus Ewerbring, Franklin T. Luk

Proceedings Volume 0977, Real-Time Signal Processing XI; (1989) https://doi.org/10.1117/12.948572
Event: 32nd Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1988, San Diego, CA, United States

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.

Citation Download Citation

L. Magnus Ewerbring and Franklin T. Luk "Canonical Correlations And Generalized SVD: Applications And New Algorithms", Proc. SPIE 0977, Real-Time Signal Processing XI, (16 December 1989); https://doi.org/10.1117/12.948572

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