Canonical correlation for stochastic processes

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Functional Data Analysis (2016, background): “An alternative way to get around the above ill-posed problem is to restrict the maximization in (3) and (4) to discrete l 2 spaces that are restricted to a reproducing kernel Hilbert space instead of working within the entire L 2 space (Eubank & Hsing 2008).”
Optimal-order bounds on the rate of convergence to normality in the multivariate delta method (2009, background): “ RSPCC, ^ˆ2, by replacing R jkin (4.54) with S jk, where S jk= jS k; S:= Y Y Y Y; Y := 1 n P i Y i; and Y Y := 1 n P Y i Y i; thus, Sis the sample covariance operator of the random vector Y. See e.g. [23,38] for discussion and results on the use of canonical correlations in functional data. Next den”
An RKHS formulation of the inverse regression dimension-reduction problem (2009, background): “Ramsay and Silverman (2005), Dauxois, Ferré and Yao (2001) and Ferré and Yao (2003, 2005)].”
Functional linear regression via canonical analysis (2010, background): “Substantial extensions and connections to reproducing kernel Hilbert spaces were recently developed in Eubank and Hsing (2008); for other recent developments see Cupidon et al. (2007).”