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Canonical coordinates and the geometry of inference, rate, and capacity

Date

2000

Authors

Mullis, Clifford T., 1943-, author
Scharf, Louis L., author
IEEE, publisher

Journal Title

Journal ISSN

Volume Title

Abstract

Canonical correlations measure cosines of principal angles between random vectors. These cosines multiplicatively decompose concentration ellipses for second-order filtering and additively decompose information rate for the Gaussian channel. Moreover, they establish a geometrical connection between error covariance, error rate, information rate, and principal angles. There is a limit to how small these angles can be made, and this limit determines channel capacity.

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Subject

filtering
canonical correlations
channel capacity
canonical coordinates
information rate

Citation

Associated Publications