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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Rights Access
Subject
filtering
canonical correlations
channel capacity
canonical coordinates
information rate