Randomized Quadrature with Periodic Kernels: Applications to Cavalieri Volume Estimation
Image Analysis and StereologyThis paper studies randomized algorithms for unbiased numerical integration of d-dimensional periodic functions using kernel-based quadrature rules, with particular emphasis on rules induced by periodic radial basis function (RBF) kernels.
Francisco Javier Soto Sánchez
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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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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
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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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Reproducing kernels in separable Hilbert spaces [PDF]
Pacific Journal of Mathematics, 1968 openaire +3 more sources
Detection of Interaction Effects in a Nonparametric Concurrent Regression Model. [PDF]
Entropy (Basel), 2023 Pan R, Wang Z, Wu Y.
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Deep Hybrid Multimodal Biometric Recognition System Based on Features-Level Deep Fusion of Five Biometric Traits. [PDF]
Comput Intell Neurosci, 2023 Safavipour MH, Doostari MA, Sadjedi H.
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Iterative sparse interpolation in reproducing kernel Hilbert spaces [PDF]
, 2001 The problem of interpolating data in reproducing kernel Hilbert spaces is well known to be ill-conditioned. In the presence of noise, regularisation can be applied to find a good solution. In the noise-free case, regularisation has the effect of over-smoothing the function and few data points are interpolated.
Dodd, T.J., Harrison, R.F.
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