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The task of curvature estimation from discrete sampling points along a curve is investigated.
In the case of discrete sampling, these functions can be shown in Eqs.
Next we outline the discrete sampling theorem, which constitute the data imputation scheme presented here.
Recording and storing such data require discrete sampling in both time and space.
We have developed a data-driven method to reconstruct probability densities from discrete sampling by computer simulations.
It can be conceptually modeled as an ADC operating at Nyquist rate, followed by random discrete sampling operation[14].
Discrete sampling schemes represent an attractive alternative for generating ensembles of conformers consistent with spatial restraints derived from empirical data.
This limitation substantially complicates the design, optimization, assembly, and evaluation image quality of the coupled discrete sampling imaging system.
Based on the knowledge of the generalized impulse response and transfer function, discrete sampling filter models are derived.
By projecting the set of all neighborhoods of a certain size which compose an image we obtain a discrete sampling of a surface.
In this paper two spectral methods for data imputation, originating from the discrete sampling theorem, are introduced to air quality time series with missing data.
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