Characterization of the traces on the boundary of functions in magnetic Sobolev spaces
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Achieving accurate interpolation is an important requirement for many signal-processing applications. While nearest-neighbor and linear interpolation methods are popular due to their native GPU support, they unfortunately result in severe undesirable artif ...
Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this problem; the currently available methods, however, are hard to deploy for large-scale inter ...
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This paper addresses the problem of the interpolation of 2-d spherical signals from non-uniformly sampled and noisy data. We propose a graph-based regularization algorithm to improve the signal reconstructed by local interpolation methods such as nearest n ...
This paper addresses the problem of interpolating signals defined on a 2-d sphere from non-uniform samples. We present an interpolation method based on locally weighted linear and nonlinear regression, which takes into account the differences in importance ...
An approximate analytical solution of the Hairsine-Rose model of erosion is obtained by interpolation of asymptotic expressions for large times and great distances. The solution, when erosion is initiated by rainfall impact, is both simple and accurate. Th ...
Classical digital signal processing (DSP) lore tells us the tale of a continuous-time primeval signal, of its brutal sampling, and of the magic sinc interpolation that, under the aegis of bandlimitedness, brings the original signal back to (continuous) lif ...
We prove several results related to local proofs, interpolation and superposition calculus and discuss their use in predicate abstraction and invariant generation. Our proofs and results suggest that symbol-eliminating inferences may be an interesting alte ...
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We study the geometrical properties of scale-invariant two-field models of inflation. In particular, we show that when the field-derivative space in the Einstein frame is maximally symmetric during inflation, the inflationary predictions can be universal a ...
The E* algorithm is a path planning method capable of dynamic replanning and user-configurable path cost interpolation, it results in more appropriate paths during gradient descent. The underlying formulation is based on interpreting navigation functions a ...