Some Remarks on Reproducing Kernel Krein Spaces
, 1991 The one-to-one correspondence between positive functions and reproducing kernel Hilbert spaces was extended by L. Schwartz to a (onto, but not one-to-one) correspondence between difference of positive functions and reproducing kernel Krein spaces.
Alpay, Daniel
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Optimal approximation in Hilbert spaces with reproducing kernel functions
, 1970 Characterisations of optimal linear estimation rules are given in terms of the reproducing kernel function of a suitable Hilbert space. The results are illustrated by means of three different, useful function spaces, showing, among other things, how ...
F. M. Larkin
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The Zero-Removing Property and Lagrange-Type Interpolation Series
, 2011 The classical Kramer sampling theorem, which provides a method for obtaining orthogonal sampling formulas, can be formulated in a more general nonorthogonal setting.
M. A. Hernández-Medina +5 more
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Structured functional additive regression in reproducing kernel Hilbert spaces. [PDF]
J R Stat Soc Series B Stat Methodol, 2014 Zhu H, Yao F, Zhang HH.
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Backward shift invariant subspaces in reproducing kernel Hilbert spaces
, 2020 In this note, we describe the backward shift invariant subspaces for an abstract class of reproducing kernel Hilbert spaces. Our main result is inspired by a result of Sarason concerning de Branges-Rovnyak spaces (the non-extreme case).
Mashreghi, Javad +2 more
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Combining genomic and genealogical information in a reproducing kernel Hilbert spaces regression model for genome-enabled predictions in dairy cattle. [PDF]
PLoS One, 2014 Rodríguez-Ramilo ST +2 more
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Utilizing Kernel Adaptive Filters for Speech Enhancement within the ALE Framework
Iranian Journal of Electrical and Electronic Engineering, 2017 Performance of the linear models, widely used within the framework of adaptive line enhancement (ALE), deteriorates dramatically in the presence of non-Gaussian noises. On the other hand, adaptive implementation of nonlinear models, e.g.
G. Alipoor
doaj
Reproducing kernel hilbert spaces regression methods for genomic assisted prediction of quantitative traits. [PDF]
Genetics, 2008 Gianola D, van Kaam JB.
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Ridge Regression Learning Algorithm in Dual Variables
, 1998 In this paper we study a dual version of the Ridge Regression procedure. It allows us to perform non-linear regression by constructing a linear regression function in a high dimensional feature space.
C. Saunders +5 more
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