Kernel density estimation (KDE) is a versatile nonparametric approach to infer continuous probability distributions from finite samples. By superimposing smooth kernel functions—most commonly Gaussian ...
Reproducing kernel Hilbert space method is utilized in this paper as an efficient approach to solve singular fourth order ...
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